Qualitative Research in Male Infertility

Qualitative research methods represent a valuable tool for investigating the entirety of the experience of male infertility evaluation, diagnosis, and treatment. Qualitative research is rigorous and thorough and well adapted for studying the complex field of infertility and reproductive health. Knowledge gained from qualitative research methods can undoubtedly inform clinical practice and improve support for individuals and couples affected by male factor infertility.

Key points

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Clinical and basic science research are limited in their ability to address the multifactorial challenges involved in the access and utilization of health care services for male factor infertility.
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Qualitative research produces descriptive data that the researcher must then interpret using rigorous and systematic methods of transcribing, coding, and analysis of trends and themes.
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Robustness and research integrity are just as important in qualitative research as in other forms of research and are assessed by specific criteria, including trustworthiness, credibility, applicability, and consistency.

Introduction

A diagnosis of male factor infertility has a tremendous impact on the physical and emotional health and quality of life of affected couples. ^, Despite this, the male partner is often overlooked in the evaluation and treatment of a couple’s infertility. In fact, male infertility is underrepresented as a disease, both scientifically and socially. Several barriers to access to care for male infertility have been described. Foremost among these is a lack of scientific data and literature that define the scope of the male infertility problem. Health care providers and the general public, alike, have misperceptions about the prevalence, severity, and impact of male factor infertility, which compromises the quality of care for affected couples, as well as the health and reproductive outcomes stemming from treatment.

Discoveries resulting from clinical and basic science research have led to numerous advances in male reproductive health, ranging from enhanced understanding of the genetic basis of male factor infertility, to optimal management of hypogonadal men, and the development of surgical techniques for surgical sperm extraction in the setting of nonobstructive azoospermia. Indeed, such advances have made paternity possible for a substantial proportion of men previously considered infertile and tremendously improved quality of life for affected couples.

However, clinical and basic science research are limited in their ability to address the multifactorial challenges involved in the access and utilization of health care services for male factor infertility. The inability to recruit patients to participate in a randomized controlled trial comparing varicocelectomy to intrauterine insemination is a humbling reminder of the limitations of quantitative research alone. Complementary approaches, such as qualitative research, mixed methods research, and/or health services research, can be helpful in identifying barriers in access to male infertility care, improving the delivery and quality of care for male factor infertility, and improve patient satisfaction.

This article explores the role of qualitative research in male infertility, including current and future applications.

Quantitative versus qualitative research

Quantitative research uses numerical data to identify large-scale trends and statistical operations to determine causal and correlative relationships between variables. In contrast, qualitative research is a scientific method of observation to gather nonnumerical data in order to understand individuals’ beliefs, experiences, attitudes, behavior, and interactions. Qualitative research produces descriptive data that the researcher must then interpret using rigorous and systematic methods of transcribing, coding, and analysis of trends and themes.

As such, qualitative research is ideally suited for investigating how or why a certain phenomenon occurs, rather than how often. This approach lends itself well to creating new theories using the inductive method, which can then be tested with further research. When used together, the combination of qualitative and quantitative research has the potential to more comprehensively evaluate and address a research problem, compared with either approach alone.

Qualitative research methodology

Five different qualitative research methods have been described, with Grounded Theory, Ethnography, and Phenomenology being the most common approaches ( Table 1 ). Data collection involves direct observations, interviews, and examination of existing documents and may be completed via individual interactions, focus groups, structured or open-ended surveys, or some combination of these techniques, depending on the study question. For example, the researcher may use “small-group discussions” for investigating beliefs, attitudes, and concepts of normative behavior; “semi-structured interviews” to seek views on a focused topic or an institutional perspective; “in-depth interviews” to understand a condition, experience, or event from a personal perspective; and “analysis of texts and documents,” such as government reports, media articles, Web sites or diaries, to learn about distributed or private knowledge.

Table 1

Qualitative research methods

Method	Description	Sample Size	Data Collection
Ethnography	Researchers immerse themselves in the study environment as “participant observers” to gain an in-depth understanding of the environment from the study participants’ point of view	—	Observation and interviews
Narrative	Researchers weave together a sequence of events or experiences, as related by one or more participants, to form a cohesive story or narrative	1–2	Stories from individuals, and documents
Phenomenologic	Researchers attempt to understand participants’ experience of an event or activity as well as the meaning participants ascribe to that event	5–25	Interviews, then thematic analysis
Grounded theory	Researchers explore the explanation or theory behind an event, based on the study data	20–60	Interviews, then open and axial coding
Case study	Researchers seek a detailed understanding of an event by examining multiple data sources	—	Interviews, documents, reports, observations

Qualitative data analysis

Qualitative research yields mainly unstructured, text-based data and may include a variety of multimedia materials. Data analysis is the part of qualitative research that most distinctively differentiates it from quantitative research methods. It is not a technical exercise as in quantitative methods, but more of a dynamic, intuitive, and creative process of inductive reasoning, thinking, and theorizing ( Table 2 ). Analyzing qualitative data predominantly involves coding or categorizing the data in order to identify significant patterns or recurrent themes or topics, which may be of interest to the researcher.

Table 2

Overview of qualitative data preparation and analysis

Step 1: Become familiar with the data	Transcribe the data, if applicable. Read and review the data several times in order to become familiar with it. Start looking for basic observations and patterns.
Step 2: Revisit research objectives	Revisit the research objective and identify the questions that can be answered through the collected data.
Step 3: Develop a framework	Identify broad ideas, concepts, behaviors, and assign labels/codes to them in order to organize them into groups. This is helpful for structuring the data.
Step 4: Identify patterns and connections	Start identifying themes, looking for the most common behaviors or responses from study participants, identifying patterns that can answer research questions, and finding areas that can be explored further.