Good listening: A key element in establishing quality in qualitative research

Abstract

What is “good” qualitative research? Considerable literature articulates criteria for quality in qualitative research. Common to all these criteria is the understanding that the data gathering process, often interviews, is central in assessing research quality. Studies have highlighted the preparation of the interview guide, appropriate ways to ask questions, and especially the interaction between interviewer and interviewee. To a lesser extent, qualitative scholars mention the importance of the interviewer’s listening abilities in obtaining the interviewee’s cooperation. Based on results of listening studies in the fields of psychology and organizational behavior, we argue that good listening is crucial for assessing the quality of qualitative research, yet remains a blind spot in qualitative data gathering. Drawing on our experience as qualitative researcher and listening researcher, we present practices for enhancing good listening in qualitative research, thereby enabling researchers to calibrate themselves as research instruments and obtain richer data.

Keywords

Qualitative listening criteria quality interview

Introduction

Historically, qualitative research has been viewed as “soft” science and criticized for lacking scientific rigor compared to quantitative research (Cope, 2014). Considerable efforts have been invested in determining criteria to assess the quality of qualitative research (Roulston, 2010), arguing that qualitative research strives for the highest possible quality (Attride-Stirling, 2001; Lincoln and Guba, 1985; Walby and Luscombe, 2017). There has also been continuous debate and even strong disagreements about the content of the criteria for evaluating such quality (e.g., Cypress, 2017; Lub, 2015; Mays and Pope, 2020; Whittemore et al., 2001).

Yet, qualitative researchers agree regarding the fundamental importance of collecting rich data (Charmaz, 2014; Lune and Berg, 2016), most commonly via personal interviews (Tjora, 2018). However, while the literature asserts that rich data are the result of the initial rigorous design of the research procedure—for example, by careful preparation of the interview guide and the wording of questions (Forrester and Sullivan, 2018)—less attention is given to the central element: the interaction between interviewee and interviewer (Mason, 2017). Too often, qualitative research textbooks jump directly from the interview planning stage to the analysis and theory development stage (Gerson and Horowitz, 2002), paying little attention to the interview procedure itself.

In those cases where scholars do attend to the importance of the interaction within the interview situation, they frequently emphasize the centrality of listening, which is crucial for establishing rapport (Lune and Berg, 2016), delving beneath the surface of subjective life (Charmaz, 2014), allowing for the emergence of complexities and uncertainties in interviewees’ experiences (Mercieca et al., 2021), and consequently collecting the rich data fundamental to qualitative research (McClelland, 2017). The current article aims to shed light on this central but frequently neglected element within the data collecting phase, namely, interpersonal listening.

Listening studies demonstrate that good listening is a major part of the interaction between a listener and a speaker. Numerous findings suggest that the insights of these quantitative studies could also be highly relevant to the interaction between interviewer and interviewee in the context of qualitative research. Good listening increases not only rapport between interviewer and interviewee (Bavelas et al., 2000), but also authenticity (Shannon, 2011), speech fluency (Bavelas et al., 2000; Pasupathi et al., 1998), trust (Ramsey and Sohi, 1997), self-disclosure (Weber et al., 2004), liking (Huang et al., 2017), open-mindedness (Itzchakov and Kluger, 2017), and self-insight, to name but a few benefits. We therefore argue that, when assessing the quality of qualitative research, good listening should be considered a central criterion and an important research measure in efforts to establish trustworthiness, credibility, and rigor. Going one step further, we offer here tools that can enable qualitative researchers to enhance the quality of their listening abilities and, consequently, the quality of their data gathering.

After reviewing quality criteria in qualitative research, with a focus on the importance of gathering rich data, the centrality of the researcher as an instrument, and the interviewee–interviewer interaction, we review listening studies and highlight their relevance to the data-gathering stage in qualitative research. Rooted in the evidence gathered in those listening studies, we then propose several practices for enhancing the quality of listening in qualitative research in general and personal interviews in particular. The contribution of the article is thus twofold. First, we highlight the construct of listening in the process of data gathering in qualitative research, based on evidence from listening studies. This constitutes a further milestone in establishing the understanding that qualitative research based on solid and thick data is as scientific as any other research method. Second, we suggest practices based on our experience as a qualitative researcher and listening researcher, thus responding to Morse’s (2020:4) recent claim that ‘excellent research requires excellent interpersonal skills in order to obtain good data.’ Specifically, we go beyond a simple checklist to offer practical listening tools to researchers that can improve their data quality and thus their research as a whole. In offering these practices, we do not suggest that good listening aims to overcome bias or to achieve neutrality in research, nor that avoiding bias is a desired goal. Rather, by highlighting the importance of listening, this article corroborates recent work about listening as a crucial component in the researcher–participant interaction (Mercieca et al., 2021), essential for the co-construction of knowledge (Mercieca and Mercieca, 2013).

The quality of qualitative research

The debate over quality criteria and the centrality of thick description

Establishing criteria for quality is essential in any scientific endeavor. Such criteria are a central theme in the qualitative research literature, within the effort to refute the perception that qualitative research is unscientific or merely exploratory (Denzin and Lincoln, 2008). Nonetheless, it is challenging to develop criteria to assess quality in qualitative research (Roulston, 2010), due to the necessity to incorporate rigor and subjectivity, as well as creativity, into the scientific process (Whittemore et al., 2001). Numerous suggestions have been made over the last few decades as those working within the interpretive perspective have struggled to articulate quality criteria in qualitative research. In the current review, we do not intend to map all existing variations of such criteria but rather highlight some commonalities, namely, emphasis on the centrality of thick description, which ultimately yields rich data. This will set the stage for identifying the importance of listening as a criterion of quality.

The most common criteria of quality in qualitative research have been proposed by Lincoln and Guba (1985; see also Guba and Lincoln, 1989), who identified the overall goal of trustworthiness. These criteria are credibility, transferability, dependability, and confirmability, respectively, equivalent to the quantitative criteria of internal validity, external validity (or generalizability), reliability, and objectivity. They argue that transferability requires thick description, which is essential for those interested in transferring the original findings to other contexts or individuals.

Drawing on Guba and Lincoln’s criteria, Whittemore et al. (2001) have offered secondary criteria: explicitness, vividness, creativity, thoroughness, and congruence. Vividness encompasses the presentation of rich, thick description, while thoroughness refers to a full exploration of the phenomenon, that is, thorough data collection. Moreover, they offer several techniques to demonstrate validity. Within the phase of data-generating, the technique of prolonged engagement is essential to foster rich, detailed responses, and it must involve the building of trust and rapport with research participants.

More recent models for determining quality in qualitative research suggest that qualitative researchers should return to the more common terminology of the social sciences, using rigor, reliability, validity, and generalizability as criteria for determining the trustworthiness of qualitative research (Morse, 2015). Morse’s (2015) recommendation to achieve rigor includes, among others, prolonged engagement, persistent observation, and thick, rich description. In a similar vein, Tracy (2010) offers eight “big-tent” criteria for excellent qualitative research (Tracy, 2010; Tracy and Hinrichs, 2017), including rich rigor and credibility. Rigor is demonstrated through careful attention to detail, methodological thoroughness, the precision of evaluation, and the generation of requisite variety regarding data richness and complexity. In describing the criterion of credibility, Tracy draws on Geertz’s (1973) observation that one of the most important means of achieving credibility in qualitative research is a thick description. The importance of thick data for research in general is aptly summarized by Charmaz:

The quality and credibility of your study starts with the data. The depth and scope of data make a difference. A study based upon rich, substantial and relevant data stands out…Readers and reviewers will see your study as a serious effort and you will have a strong foundation from which to speak… A researcher can rarely make persuasive, much less definitive, statements from limited data (2014:18).

While the literature clearly maintains that rich data are an essential criterion of quality in qualitative research, and that thick description provides researchers with a detailed account upon which to base their arguments (Tracy and Hinrichs, 2017), it is less clear how to obtain such thickness. Morse (2015), for example, suggests that collecting rich data is more than simply obtaining good data from one participant; rather, thick and rich data refer to the entire dataset, so that data quality is also associated with the number of interviews and/or participants.

With respect to interview studies, scholars tend to discuss the possibilities of achieving rich data within the interview context. They usually focus on outlining the interview steps, developing interview guidelines, making decisions about question order, content, style, the wording of questions, and the like (Lune and Berg, 2016). Many important and broadly cited practical guides offer examples of how best to frame the questions so as to yield the thickest description (e.g., Charmaz, 2014; Mason, 2017; Tjora, 2018). However, less attention is given to the fact that, even when all considerations have been made to ensure questions are articulated to perfection, the data produced in the interview are still mainly a result of the researcher–participant interaction (Schober, 1992). The interaction during the interview, and the crucial role of the researchers’ listening within this interaction, is essential for obtaining rich data.

The researcher as an instrument and the interaction during the interview

While there are many methods for conducting qualitative research, the (in-depth) interview is considered the most common one (Roulston, 2010). Gubrium and Holstein (2002) argue that we live in an “interview society.” Indeed, everyone has received some training and has some experience in interviewing. Thus, one could assume that, as everyone has tacit training in both asking questions and answering them, the research interview is just another natural communication situation (McClelland, 2017). But the research interview is far from a natural communication exchange (Lune and Berg, 2016; Morse, 2020). A good interview yields data that have enough quality to establish the research arguments—in other words, a good interview yields rich data.

While the literature is unanimous in the understanding that the questions asked during the interview are a major element in achieving thick description, it also highlights the importance of the interactive relationships between the interviewer and interviewee and their implications for the interview outcomes (Morse, 2020). Holstein and Gubrium (2011) define the interview situation as “active,” in the sense that interviewing is unavoidably interactional and constructive and is actively productive of its result. In a similar manner, Lune and Berg (2016) suggest the Dramaturgical Model of interviewing, according to which both researchers and participants in the interview situation take on defined “social roles” and “perform” certain kinds of interactions throughout the interview.

Drawing on the understanding that the interviewer profoundly influences the interview situation, it becomes clear that good interviewing is in no small part about the interviewer’s skills (Mason, 2002; Morse, 2020). Thus, if researchers are interested in conducting an interview that goes beyond ordinary conversation, delving beneath the surface of the described experiences (Charmaz, 2014), we have to turn the spotlight on the researcher, not only as the person who asks the questions or as a tool to convey the interviewees’ stories, but as an equal producer of the interview data. Thus, to achieve the goal of good research, the researcher needs to be well calibrated. We focus on the element of listening as part of this calibration.

Calibrating the research tool

In qualitative studies, the researcher is a main research instrument (Denzin and Lincoln, 2008; Morrow, 2005). As such, excellent qualitative research requires excellent interpersonal skills (Morse, 2020). As in all sciences, calibrating the research instrument is a fundamental stage in collecting valid and reliable data. In most cases, such calibration is a simple or at least a straightforward operation: the biologist has precise guidelines on how to calibrate the microscope; even a social scientist who conducts quantitative research should follow well-known steps to validate the questionnaire. However, in qualitative research, where the researcher is the main instrument, calibration and the development of the required interpersonal skills is a much more complex task. As demonstrated above, many important “how-to” qualitative guides maintain that the researcher should make thorough preparations and exercise several practices before conducting interviews.

Surprisingly, very few qualitative guides on preparation have focused directly on the element of listening in qualitative research (Jack, 1999; McClelland, 2017). This is surprising, given that listening is fundamental to gathering rich data (Charmaz, 2014), establishing rapport with interviewees (Lune and Berg, 2016), and encouraging participants to share their inner life in a way that makes them feel they are not being judged and can share experiences and beliefs that might be less socially accepted (Lavee, 2016). The quality in which the interviewer listens shapes the nature of the knowledge produced (Mason, 2002).

While listening is recognized as an important aspect of qualitative research, it is frequently discussed in a very limited manner, more implicitly than explicitly. In most cases, no precise explanations are given as to how researchers should improve their listening skills (Flick, 2018). For example, Mason (2017) urges readers to “really listen to what people are saying” during the interview and argues that “[m]ost people need a great deal of practice in this.” She says to ‘be critically constructive with yourself: were you really listening and attending to what was being said to you?’ (2017:126). She does not, however, define what it means to really listen or describe how to do so. Lune and Berg (2016) do offer some explanation of how to listen better in the interview, instructing researchers to “demonstrate aware hearing”:

Be sure to offer the subjects appropriate nonverbal responses. If they describe something funny, smile. If they tell you something sad, don’t smile. If they say that something upsets them, empathize. Do not present yourself as uninterested or unaware (2016:87).

Still, the qualitative literature lacks more direct examples of “good listening.” This lacuna can be filled by drawing on findings from the listening literature. Learning from listening studies can allow qualitative researchers to push their everyday listening further, helping them acknowledge the complexities and multiplicity in the subjective thinking of research participants and thus achieve the thick description essential for deciphering the meaning-making of individuals.

Good listening

The definition of good listening

Individuals tend to have a unified perception of how they are being listened to and to evaluate the quality of the listening on a single continuum from poor to excellent (Lipetz et al., 2018). The construct of listening in an interpersonal context is multi-faceted, and three main facets of good listening have been identified: attention, comprehension, and relational components (Itzchakov, 2020; Kluger et al., 2021). Attention refers to being fully present with the speaker and avoiding internal and external distractions (Ames et al., 2012). Comprehension refers to the extent to which listeners signal that they understand the speaker. Finally, the relational facet refers to the good intentions that the listener needs to have toward the speaker. This includes acceptance, empathy, and a non-judgmental approach (Itzchakov et al., 2017; Rogers and Roethlisberger, 1991). Rogers (1980) conceptualized good listening as a genuine presence and effort to understand what the other person is saying, being empathetic and non-judgmental while regarding the other with respect and curiosity.

Listening-induced effects on speakers/interviewees

When speakers perceive good listening, they experience numerous emotional, cognitive, and behavioral benefits (e.g., Bodie, 2012; Itzchakov et al., 2018; Pollak et al., 2011). Conversely, poor listening can damage the quality of the conversation and impair the speakers’ thinking process (e.g., Pasupathi and Rich, 2005; Pasupathi and Hoyt, 2010).

Studies in organizational behavior have pointed to some of the effects of listening quality on speakers. Specifically, employees’ listening experience is positively associated with their job satisfaction (Tellis-Nayak, 2007), commitment to the organization (Reed et al., 2016), better performance (Bergeron and Laroche, 2009), and more organizational citizenship behavior (Lloyd et al., 2015), to name just a few. Listeners impact the conversation through backchannel behaviors, which consist of nonverbal and verbal signals. Examples of nonverbal signals include head nods that convey agreement with the speaker and a willingness to listen more; facial expressions that express interest and surprise or disagreement with the speakers’ messages; and body movements that signal interest, such as leaning forward, or lack of interest (or disagreement), such as leaning back and folding one’s arms. Verbal signals include questions that convey understanding (or lack thereof) and completion of the speakers’ sentences (Bavelas et al., 2000).

Speakers are significantly affected by backchanneling. When they perceive such behaviors as constructive, they experience good listening and feel understood. Consequently, their speech fluency improves (Bavelas et al., 2000). When they perceive backchannel behaviors as destructive, their stories become shorter and less fluent and lack a coherent structure (Brennan et al., 2010; Pasupathi and Billitteri, 2015). In the context of qualitative interviews, such factors can strongly impact the researcher’s ability to obtain thick description.

Furthermore, and most relevant to the need to delve “beneath the surface” in qualitative interviews (Charmaz, 2014), good listening reduces the defensiveness of speakers and consequently increases cognitive flexibility (Itzchakov, 2020; Itzchakov et al., 2017). Specifically, when speakers share their attitudes with a listener who demonstrates high quality listening, they report lower levels of social anxiety (i.e., apprehension from being evaluated negatively), which in turn makes them more open to alternative viewpoints about the attitudinal topic they are discussing. This process results in attitudes that are more complex and less extreme (one-sided). Speakers become aware of conflicting aspects of their attitude and can tolerate this contradiction.

Empirical evidence supports the assumption that good listening increases speakers’ psychological safety (Castro et al., 2016; Itzchakov et al., 2016). An important correlate of psychological safety is trust. Frequently referred to as “rapport” relations, trust between interviewer and interviewee is considered a foundation of any successful qualitative endeavor. Research suggests that speakers who experience high quality listening put more trust in their listener in the context of negotiation and sales (Ramsey and Sohi, 1997; Itani et al., 2019). A meta-analysis of nine studies and about 30,000 participants indicates that the average association between perception of good listening and trust tends to be quite strong (Itzchakov, 2020).

The above findings demonstrate that rich data, which constitute the foundation of all scientific research, are, among other things, substantially a consequence of good listening. Therefore, when assessing the quality of qualitative research, the element of listening must be evaluated. We argue that listening should not only be given more attention in the qualitative research literature, but should be considered a major element impacting the quality of the overall research venture. Moreover, good listening is an effortful process that requires training (Itzchakov and Kluger, 2017). The following section presents tools enabling qualitative researchers to hone their listening skills.

Listening practices for enhancing the quality of qualitative research

While there is consensus that the quality of qualitative research is determined by the ability to obtain thick description from participants, less is known about what counts as thick description. Following Mercieca and Mercieca (2013), we argue that it is not only an outcome of the interviewee’s willingness to share experiences and thoughts, but also the researcher’s ability to acknowledge the uncertainties and complexities in the participants’ worlds in an effort to disentangle their ‘messes of reality,’ as Law (Law, 2004: 2) puts it:

[M]uch of the world is vague, diffuse or unspecific, slippery… change like kaleidoscope… if we want to think about the messes of reality at all then we’re going to have to teach ourselves to think, to practice, to relate, and to know in new ways.

Combining the main insights from a decade of experience in qualitative interviewing with both dominant and weakened populations (first author), as well as in training interviewers, with the knowledge and experience of a listening researcher (second author), we now apply findings from listening studies in various fields to the context of the qualitative research interview, with the aim of offering researchers ways to obtain thicker, richer data, resting on the understanding that high quality listening creates a safe space facilitating the emergence of the speaker’s contradictions and paradoxes (Snelling, 2005). To do so, we present several listening practices that can be used by qualitative researchers.

Before delving into these practices, it is important to note that our aim is neither to offer a checklist nor to imply that the skillful interviewer asks good questions while carefully minimizing bias and researcher influence by taking a neutral role—as is common in more positivist and neopositivist approaches (Roulston, 2010). Rather, we suggest ways for researchers to calibrate themselves as research instruments that are essential for generating knowledge construction during the interaction with the interviewee.

Clear your mind and give full attention to the interviewee

Good listening begins with being fully present for the speaker. You need to withhold your thoughts about what you want to say, contribute, control, and direct, and put aside your own concerns. You have to leave your agenda at the door and regularly remind yourself to refocus: this interaction is not about you, your impressions, or your worth. You need to give your full attention to the speaker, that is, to settle your mind, focus, and be present for your interviewee. If you feel too distracted, you might consider postponing the interview to a time when you can truly listen. This may be difficult under real-life constraints, but the alternative might be damage to trust relations with the interviewee and a dull interview, yielding a thin description.

Making eye contact is one main practice to ensure your attention: as part of how they assess another’s attention, interviewees look at their listeners every few seconds to see if they are still with them. It is therefore vital to maintain constant eye contact with the speaker (Bavelas et al., 2002). These moments are crucial for helping the interviewee to introspect and self-explore. Constant eye contact from the interviewer increases the interviewee’s psychological safety (Castro et al., 2016).

If you notice you have lost track of the conversation because you were mindless or in your own thoughts, apologize and ask the speaker to repeat. Do not be afraid to upset the interviewee or lose his or her trust. On the contrary, by admitting your lapse, you signal that what the speaker says is crucial to you and that you do not want to miss any information.

Avoid judgment and evaluation

In addition to clearing your mind, you need to free yourself of subjective judgments and evaluations, to listen without jumping to conclusions or interpreting the content you hear during the interview (Rogers, 1957). In many cases, the listener’s initial perspective is different from the meaning the speaker is trying to convey (Lavee, 2017). You therefore need to listen to your own inner dialogue while you are listening to the speaker. This process has been labeled as a “second channel” of listening to oneself (Egan, 2013). You should notice, but not articulate, your judgments, criticisms, and disagreements. When you notice judgmental thoughts, do not dwell on them but rather push them aside. Note that good listening is not the same as agreeing. The interviewer does not have to embrace the interviewee’s views but rather to agree with the latter’s freedom to hold and express them (Rogers, 1962). A non-judgmental approach facilitates an atmosphere of safety, protection, and acceptance. Speakers can explore their perceptual field more fully and discover deeply contradictory experiences (Rogers, 1951). Such an environment acknowledges uncertainties, which is essential to the researcher’s further engagement with participants’ lived experience (Mercieca and Mercieca, 2013).

Reflect and validate the interviewee

Good listeners provide reflection and validation (Nemec et al., 2017). One of the most important antecedents of good listening is providing speakers with reflections about the content they share (Kluger and Nir, 2010). Reflection entails a short summary of the content that the speaker shared, preferably in the speakers’ own words. Reflection conveys an intention to understand the speaker, which is a core need (Reis et al., 2017). At the end of the reflection, ask, “Did I miss anything?” and “Is there anything else?” Such questions after a reflection help the speaker gain clarity about their thoughts and develop new insights. Even if the response is, “That’s not what I meant,” the speaker will sense your interest and willingness to struggle to grasp their meaning and will feel they are being listened to. Moreover, the listener will gain novel information because speakers tend to complete the content that the listener missed (Goh, 2012). When you think your meaning and theirs differ, try to listen with the interviewee’s ‘dictionary’ (Jennifer Grau, personal communication,¹ 6 May 2020) in an attempt to triangulate their meaning.

Validation entails conveying acceptance of the speakers’ thoughts, feelings, and behavior (Lynch et al., 2006). Validation makes speakers feel they are worthy of attention (Kim and Kim, 2013). Examples of validation include nonverbal behaviors such as nodding and verbal signals such as thanking interviewees for sharing their experience. Such validation is particularly important when speakers bring up uncertainties and doubts. Good listeners try to understand the speaker’s perspective and paraphrase content that conveys ambivalence, allowing speakers to become aware of and explore internal conflicts and contradictions (Rollnick and Miller, 1995). Allowing such contradictions to emerge within the interview interaction is crucial, as it reflects what Billig et al. (1988) call “dilemmatic thinking,” arguing that contradictory thoughts may coexist in a person’s mind. Yet, people seem to dismiss this “mess” (Law, 2004), believing that only deliberate actions and thoughts matter. Studies have found that speakers exposed to high quality listening were able to tolerate the presence of such contradictions, experiencing them without their usual associated discomfort (Itzchakov et al., 2017). Using good listening, then, interviewers can help interviewees shed light on and give space to that which is neither deliberate, incidental, nor spontaneous, and be open to what such thoughts and experiences tell them (Mercieca et al., 2021)

Reflect on your own listening

Listening resembles a muscle that needs to be activated (e.g., Itzchakov and Kluger, 2017; Tangirala and Ramanujam, 2012). In order to train this muscle, it is essential to reflect on your listening after an interview. That is, good listeners need to be able to observe themselves. The best way to do so is by listening to a recording of the interview. Good training might also include an outside perspective, asking a colleague or friend to listen and provide feedback regarding the interaction.

When you finish an interview, think about the opportunities you might have missed, including moments where you missed potential leads. For example, when there was silence, you may have changed the subject to avoid awkwardness instead of allowing the interviewee to introspect or ask questions that elicit elaboration (Itzchakov and Kluger, 2019). When you feel you did an excellent job listening, think about the conditions within yourself, your conversation partner, and other environmental conditions that allowed this listening to happen.

Ask (good) meaning-making questions

An interview is a process of meaning-making (Josselson and Lieblich, 1999). Each word that the interviewee uses is a microcosmos of his/her consciousness. When we speak, we assume that anyone who hears us understands what we mean, literally. However, words can have multiple meanings (Clark and Schober, 1992). Therefore, within the context of the qualitative interview, it is not sufficient to merely hear the interviewee’s words; good listening also means that you make sure you understand their meaning. In that sense, good listening is also about asking the right questions—those that encourage speakers to elaborate on their meaning and perspective (Charmaz, 2014). Thus, the right question is, first and foremost, open; it does not include possible answers (“Do you think this was right or wrong?”) nor does it provide a direction to the answer (“Would you agree that X should have behaved differently?”) (Van Quaquebeke and Felps, 2018). Good listeners ask questions that allow dilemmatic thinking (Billig et al., 1988) to emerge, reassuring speakers that contradictions, uncertainties, and lack of clarity are very much present in our lives and encouraging them to explore the “mess” (Law, 2004) in their experiences and thoughts. Good listeners ask questions that enable speakers to reveal new information about themselves outside of their awareness (Van Quaquebeke and Felps, 2018). Before asking the question, consider whether it is intended to benefit the interviewee or satisfy your own curiosity. There is also importance to how you begin the question or which question-word you choose. For example, consider the questions “how did it happen?” and “why did it happen?”. The former elicits more openness, while the latter elicits defensiveness and a need for self-justification (Trimboli, 2019).

Within the exchange of questions and answers between the interviewer and interviewee, Clark and Schober (1992) point to the phenomenon of “telescoping,” whereby interviewees assume that similar to daily conversation, they are expected to respond quickly to the question they have been asked. Therefore, their answer reflects the first thing that came to mind, yielding only surface-level description. To facilitate richer description and overcome the natural tendency for a quick, surface-level response, you should encourage speakers to spend some more time thinking through their replies. You can prompt them for a deeper response by saying, “Take your time, don’t rush with an answer.” Further, you can ask, “Do you have anything to add?” A good listener might also use silence instead of questions to avoid telescoping. By keeping silent for just a few seconds while maintaining your entire focus on the interviewee, you signal that this interaction is not an ordinary conversation between two people and that pausing for further reflection on the topic is more than welcome (Curhan et al., 2021). By giving the speaker space for further thinking, you will experience listening at a profound level, which promotes open-mindedness and self-disclosure (Sullivan and Rees, 2008).

Discussion

The focus of this article is the understanding and evaluation of “good” qualitative research. Given the subjective nature of the constructivist-qualitative approach, assessing the quality of such research is difficult. While this question has been the subject of many scholarly debates (Roulston, 2010), the centrality of “good” data is undoubtably a fundamental element in establishing quality in the research.

What, then, constitutes good data? Qualitative scholars tend to agree that thick description (Geertz, 1973) is a preliminary condition for yielding rich data (Charmaz, 2014; Lune and Berg, 2016). Indeed, much attention has been given to the data gathering stage, focusing—in interview-based studies—on preparing the interview and, to a lesser extent, the interview setting and the interaction between the researcher/interviewer and the participant/interviewee (Mason, 2017). Our main argument in this article is that, within this interaction, the element of listening is crucial for obtaining rich data and, consequently, for the overall quality of the research.

A general overview of common criteria for evaluating the quality of qualitative research revealed that rigor, trustworthiness, credibility, vividness, and reliability—to name but a few—all rely on the researcher’s ability to obtain rich data (Lincoln and Guba, 1985; Morse, 2015; Tracy, 2010; Whittemore et al., 2001). Building on this insight, we have drawn on findings from listening studies to demonstrate various aspects of good listening which are essential criteria for enhancing and assessing quality. Within this field, ample research has demonstrated that the quality of listening, and the listener’s ability to be a “good” listener, has a profound impact on the speaker’s stories. Applying these findings to the context of joint meaning-making by interviewer and interviewee in qualitative research, we argue that the interviewer has considerable influence on the interviewee and hence on the data yielded by the interview and, in turn, on the overall study outcomes. Furthermore, the key element of such influence is the interviewer’s listening abilities.

Listening is often imagined to be easy, something that everyone is good at. Many assume it merely involves nodding one’s head, not interrupting, and “remaining open” to a speaker’s answers. Most people believe they are already good listeners and do not need to practice as they have been doing it their whole lives. Listening is, therefore, often seen as a “natural” and subsequently unappreciated research practice (McClelland, 2017). However, as listening studies teach us, good listening is a difficult skill that takes both knowledge and practice. More than that, good listening is crucial to encourage participants to consider the uncertainties and complexities in their lived experiences that more accurately reflect the “mess” (Law, 2004) and contradictory thoughts (Billig et al., 1988) characterizing the real life of all people (Mercieca et al., 2021). Engaging in these complexities is essential for deciphering and making sense of people’s worlds. The practical tools we have provided to qualitative researchers thus aim at enhancing the quality of their listening abilities and, consequently, the quality of their overall research. This contributes to existing suggested listening practices by relying not only on individual experience, but also on findings from listening studies.

Beyond using the tools we have presented to improve their listening skills, enrich their data, and enhance their study outcomes, we also suggest that when qualitative researchers report on their research procedure, they should demonstrate the efforts they have made to practice good listening. This can serve as a means for readers, reviewers, and others to assess the quality of the data presented.

It should be reiterated that, in offering good listening tools, we do not suggest that good listening is intended to overcome bias nor that this should be a desired goal. Nor do we imply that, in order to improve the quality of qualitative research, one should adopt a systematic scientific approach that could be perceived as positivist or neopositivist (Roulston, 2010). Indeed, we join in Mercieca et al. (2021: 3) concern about ‘the totalitarian use of such terms [as evidence-based training], so that anything that does not fall within these parameters is seen as useless, or worse, bias, and consequently discarded.’ While our proposed tools do draw on systematic evidence from experimental studies, this should in no way diminish the crucial importance of the researcher’s intuition. Nor do we underestimate the contributions of critical or interpretive traditions. Indeed, we argue that the element of good listening is essential for the very purpose of achieving the thick description needed in inductive, constructivist methods.

Future studies

In light of findings of interpersonal differences in listening preferences among people with different personality traits (Itzchakov et al., 2014), future endeavors at exploring the element of listening in qualitative research might focus on differences between individual speakers or demographic groups in the type of listening that can optimize their willingness to share their stories. Moreover, there are differences in gender-based preferences in the amount of intimacy that a participant prefers (Charmaz, 2014), which can impact the listening process and are worth investigating. Finally, some sensitive populations, such as people who live in poverty, have “habits of hiding” (Dodson and Schmalzbauer, 2005), such that listening to them might require a different style than the one practiced in interviews with more powerful populations, such as managers.

From another angle, an important elaboration of the argument about the effect of listening in interview studies would be to examine it in other common forms of qualitative data collecting. For example, recent efforts have been directed at enhancing data collection quality in focus group research (Flynn et al., 2018), but the element of listening is rarely mentioned. As this method is common in qualitative studies, it would be interesting to learn about the effects of listening within groups in addition to a one-on-one situation.

Finally, the listening studies reported in this article are mostly laboratory experiments. Further systematic research focusing on the effect of listening should be done in the context of real-life qualitative studies. Such studies could establish a more systematic qualitative-based measure of good listening.

Footnotes

Declaration of conflicting interests

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

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This article was supported by Israel Science Foundation (grant no 460/18).

ORCID iD

Einat Lavee

Note

Author biographies

Einat Lavee is an Assistant Professor in the Department of Human Services at the University of Haifa, and Co-Director of the Research and Training Unit at the Interdisciplinary Center for the Study of Poverty and Social Exclusion. She is specialized in qualitative methods, and particularly in conducting large-scale and comparative qualitative studies. Her research interests include the welfare state and social policy, as well as class and the labor market. She specifically interested in the ways in which macro-level institutions, discourses and social imperatives shape individual working experience at the local level. Her work is published in prestigious forums such as Journal of Public Administration Research and Theory, Governance, and Journal of Social Policy. Beyond her academic work, she also advises governmental agencies on the issues of poverty and social policy, particularly among low-income workers.

Guy Itzchakov is an Assistant Professor at the University of Haifa, Department of Human Services. He obtained his Ph.D. from the School of Business Administration at the Hebrew University of Jerusalem in 2017 and was a postdoctoral fellow University of Toronto, Rotman School of Management, in 2018-2019. His focal line of research focuses on the effects of high-quality listening on facilitating change and growth in speakers, listeners, and their relationships. In addition, he conducts field studies in organizations that examine the effects of listening training on the relationship between employees and their downstream effects on organizational outcomes. Guy’s research has appeared in journals such as Personality and Social Psychology Bulletin, European Journal of Work and Organizational Psychology, Journal of Experimental Social Psychology, Applied Psychology: An International Review, Harvard Business Review, and Annual Review of Organizational Psychology and Organizational Behavior.

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