To live (code) or to not: A new method for coding in qualitative research

Abstract

Coding is an integral part of qualitative research for many scholars that use interview or focus group data. However, current practices in coding require transcription of audio/visual data prior to coding. Transcription before the coding process is an essential process for data analysis and even with meticulous detail, the nuances of nonverbal behavior found in audio and video data can be missed. In this article, we propose an alternative to coding with transcripts using a method called live coding which allows for simultaneous manual coding while listening or watching audio or video recording. We compared the method of live coding with transcript coding of text using focus group data from a perinatal telehealth group addressing depression. Based on the themes that emerged from analyzing the process, it is likely that live coding can be beneficial in preserving the voice of the participant especially used within focus group data. Live coding allowed us to see and hear the participants, an empowering process which allowed intent, context, and meaning of the words to be present in the results. Further study of live coding should include using digital tools for the analysis of qualitative data.

Keywords

Qualitative research qualitative methodology coding interviews focus group transcription audio recording video recording nonverbal behavior live coding voice of participants

Live (as in to live or to die) reads very differently than live coding (as in live animal). Text can often be misread, misinterpreted, and misunderstood. Qualitative researchers are aware of these errors that can occur in data analysis as they study the words of the participants. And yet, audio and video data continue to be interpreted after transcription, and nuances such as emotion, nonverbal communication, and context continue to be missed throughout the coding process within qualitative exploration. According to List (2007), “live coding” is “coding without transcription” and “not transcribing everything.” List proposes two methods of this approach: (1) “summarizing on the fly,” which involves listening to/viewing the recording and inserting symbols for the relevant portions and then transcribing those pieces and (2) “coding on the spot,” which requires creating a coding structure and then summarizing the video/audio content in one-minute segments and checking to see if the code is present. This paper will present a similar approach that can be used to enhance and capture the voice of the participants parallel to the process of transcription-based qualitative research. We will also use the term “live coding” to describe this method.

With access to various technology, qualitative methods have become increasingly more approachable to new researchers and cuts across multiple disciplines (Denzin and Lincoln, 2012; Flick, 2014). According to Creswell and Poth (2018), five main approaches to qualitative inquiry include narrative research, phenomenological research, grounded theory research, ethnographic research, and case study research. Interviews and focus groups are the most frequent methodological approaches used within qualitative research, especially within social work (Connolly, 2003; Gill et al., 2008). Often these include audio- or video-recording of interviews and groups, resulting in hours of data that are transcribed and then coded. The voice of the participants often interpreted by the transcriber are then reduced to words running the risk of removing the meaning behind them.

Digital coding

Using Computer Assisted Qualitative Data Analysis Software (CAQDAS) such as NVivo, Atlas.ti, Hyperresearch, ELAN, Transana, and MaxQda, the video and audio data can be analyzed to preserve the voice of the participant. Much of the current process of using CAQDAS includes uploading transcripts along with the audio/video recording and coding the transcript while listening to the recording. Although some researchers argue that with increasing availability of technology, that transcription may or may not be necessary (Saldaña, 2016).

At present, non-text data as Pennington (2018) describes include photographs, films, music, videos, social media, etc. and with using it comes its own sets of benefits and challenges. According to Pennington (2018), digital coding of non-text data should still include the following domains: theoretical underpinnings, types of data analyzed (video, photo, etc.), the scope of the analysis, and the specific data being analyzed (multiple videos, specific photographs, etc.). Using digital tools allows researchers to watch/listen to the recording and code the transcript simultaneously (Saldaña, 2016). Additionally, using methods such as videography (Pennington, 2018) allows the researcher to gather contextual information from the video clips in order to better situate the themes when coding. Those who use digital software tools have the option of directly coding video and audio data (without transcription) allowing for in-depth coding of non-verbal and participant interactions (Basit, 2010). Friese (2014) suggests that coding the video file rather than coding the transcription allows the researcher to remain connected to the digital data. However, much of current qualitative practice dictates that videos and audio recordings are transcribed into written text before they are analyzed (Davidson, 2009).

Multimodal documents which includes both text and non-text data details that information from the video are specific to the research question. This is similar in “transcribing” the video where the information regarding “the people present, their physical actions, words spoken, and facial expressions could be described at relevant time intervals” (Pennington, 2018: 20). In essence, live coding as described in this paper reflects in part these elements with a more detailed process in conjunction with text data. The focus of this paper describes live coding through manual coding (paper and pen method, using colored pens, white boards, and sticky notes) rather than using software for coding video data to further elucidate the live coding process which can later be studied using digital tools for analyzing qualitative data.

Transcription

Within the most widely used methods of qualitative data analysis, transcription is central to the process. Transcription allows researchers to read and skim the text much faster than they can listen to or watch the recording (Oliver et al., 2005; Poland, 1995). Additionally, written text provides the ease of finding keywords or themes. Methods such as grounded theory rely on this strategy to pull information from qualitative data. Further, most research outlets require text submissions which frequently include participants’ quotes.

Transcribing, though it seems to be a “straightforward technical task,” can be daunting depending on the amount of detail that is needed (Bailey, 2008). The process of transcribing itself is often “selective,” as it is not plausible to include all the nuances of audio or video speech in text (Davidson, 2009). The level of non-verbal interaction (head nodding, laughing, sarcasm, inflection); verbal representation such as minimal encouragers (“mhmm,” “yeah, right”); instances of cross-talk and the data translation (i.e. “K” vs. “Okay,” words spoken in another language, phrases that are unintelligible) can be burdensome for qualitative researchers. In addition, during the data analysis process, when listening to and reading the transcripts, the interpretation can vary based on the cultural biases of the coder or researcher. The chance for errors is high in transcription, especially if the transcribing is not completed by the primary researcher or if the transcriptionist is not part of the research team (MacLean et al., 2004). Further, Packer (2018) argues that how the transcription is formatted and laid out can influence the data interpretation. There is often a continuum of the transcription process referring to the translation that is most aligned (verbal and nonverbal) with the audio or video data (naturalism) versus those that only include verbal speech (denaturalism) (Oliver et al., 2005). Once the audio or video data are transcribed, data analysis begins. Davidson (2009) argues that transcription also includes a theoretical and epistemological stance that should be considered in the description of data analysis depending where on the continuum of naturalism and denaturalism the transcription process falls. However, critics argue that neither naturalism nor denaturalism is void of biases that impact the data analysis process and the meaning that is attributed to the participants’ voices (Oliver et al., 2005). Others argue that with the arrival of digital tools, transcription has become somewhat obsolete moving away from traditional transcribing and then coding toward coding non-text data directly (Paulus et al., 2014).

Coding

Qualitative research by nature is a cyclical, non-linear process that includes recursive data analysis. Similarly, coding is not merely naming themes, but is connecting themes back to the data and the data back to the themes (Saldaña, 2016). Although coding is not the only way of analyzing data, it is one of the more popular methods among qualitative researchers. Packer (2018) offers that coding is the data analysis process in qualitative research and similar to the process of transcription is not devoid of limitations. The author suggests that coding also takes away the voice of the participant reducing it to words and loses the connection of the joint interaction between the interviewer and interviewee. Finally, the limitation that coding “depopulates the participants” or removing the person from the participant in essence depersonalizes the process (Packer, 2018: 93).

According to Saldaña (2016), “a code in qualitative inquiry is most often a word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data” (p. 3). Coding can be done with numerous types of text and non-text data, including transcripts of interviews, images, journals, etc. The focus in qualitative research is on interpretation within the qualitative framework of these differing data, and the process varies based on the purpose and type of study being conducted (Basit, 2010).

Coding offers “slices of social life recorded in the data – participant activities, perceptions, and the tangible documents and artifacts produced by them” (Saldaña, 2016). The coding of video or audio live, rather than through transcripts, offers this “slice of social life” in a dynamic new way. Things that are often missed in transcription including tone of voice, head nodding, lack of eye contact, body posture, and other paralinguistic behavior can help to provide richer, more detailed information to the audience. In this paper, we propose an alternate way to code focus group interviews through live coding that directly codes the non-text data while still maintaining the integrity of the coding process.

Currently, most researchers use some version of the following process when using audio/video recordings in qualitative research (Marshall and Rossman, 2016):

Creating and utilizing a semi-structured interview protocol

Interviewing study participant(s) and audio/video recording

Transcribing interview(s) verbatim (depends on disciplinary practice and theoretical stance the extent to which non-verbal behaviors are transcribed)

Checking accuracy of transcript(s) by listening/watching with the transcript in hand

Using transcript(s) to begin coding (depending on theoretical framework this could include multiple readings of the transcript) or identifying patterns in the data and developing themes

○Developing codes based on theoretical approach and research design (e.g. ethnography, grounded theory)

○Creating analytical memos by the research team members

○Grouping codes or patterns into overarching categories or themes

These include at a minimum of two rounds of coding within the cyclical process. Much of the fear surrounding moving outside of traditional methods in qualitative research in the coding process is losing this recursive process. However, there are ways to preserve the process while adding new methods of approaching the data.

Live coding

For the purposes of understanding our new approach to live coding, we used focus group data from a study that used a videoconference intervention (VCI) to a group of women with mild to moderate perinatal depressive symptoms (Latendresse, 2017a). The live coding approach was used to understand the effectiveness and analyze the feedback of women’s participation in the mindfulness-based group. Below, we will provide brief information about the data used and the specific processes used by the researchers to analyze the data.

The data used for live coding included transcripts and video of three, one-hour focus groups totaling 17 participants who were providing feedback regarding their participation in a VCI mindfulness-based group for perinatal women (Latendresse, 2017b). The focus groups were conducted by one author of this paper who was the primary researcher; the others were involved exclusively in the data analysis. The focus groups included a semi-structured interview, and the process to develop broader themes reflected these questions. The group interviews were transcribed by a transcription service using a denaturalistic stance (i.e. non-verbal behaviors were not coded). Coding themes were derived during the open coding process. The team individually coded the transcripts using manual coding and met as a team to discuss if there was agreement or disagreement about the codes that were developed. The main author coded the videos at first and then manually coded the transcripts as well. This was to better understand the live coding process within a comparative model. The videos were coded first as not to be influenced by the immersion and coding of the transcripts. As the qualitative team met, further discussion led to additional codes, collapsing of codes, or rewording the codes which were then used in subsequent analysis of the transcripts. Subthemes were then developed from the videos and later compared to the codes developed from the transcript. Using grounded theory principles (developing categories of meaning from participants voice) (Corbin and Strauss, 2015), research team members completed the thematic analysis for initial codes which were derived individually (Braun and Clarke, 2006). We then met as a team to discuss the findings; these meetings were audio recorded as part of the team’s reflexive notes. Themes were then organized into groups from the individually derived themes to determine initial categories. Last, higher-order categories were developed in collaboration after a recursive look at the data. This followed open, axial, and selective coding within grounded theory. After the broader categories were derived, the coding team consulted with the primary interviewer and those that facilitated the focus groups (Latendresse, 2017b). The analysis involved immersion in the data and for comparing the processes of coding included both the video and the transcripts. Codes and themes were initially developed using the videos, and then the same immersive process was used with the transcripts.

A two-member qualitative researcher team (the coding team) was only involved in the analysis of the data-coded videos of the three focus groups. The main researcher on the coding team coded both the video and the transcript separately for each focus group for comparison purposes. The second team member coded only the videos. The themes were compared across transcripts, and the video coding to see if differences were found in the way the data was coded. The research team kept separate notes of the coding process from the data analysis, including what they found helpful and unhelpful and had regular debriefings about the data as well as the live coding process. Both members had prior education, training, and experience with qualitative research, specifically with manual coding using transcripts. The researchers had previously used transcripts as primary data with video and audio as supplemental data for clarification and accuracy checking.

As we approached the data using both transcripts and the videos, we realized that some of the subtlety of the data (i.e. nonverbals) would be lost if we used traditional methods for manual coding. For example, some of the women in the group brought their babies during the focus group which was viewed through the video recording and provided additional data (ideas of community and connection) that would have been missed in the text transcript. The women often commented on the babies and there were nonverbals associated with their babies that would have been lost which were not included within the transcripts. Since this was a VCI group, there were times that participants were engaged/disengaged that could only be noted through video interaction. This led us to using live coding for the purpose of analyzing the focus group data.

Live coding process

As the process of live coding was explored during data analysis, the coding team used the following approach as described below in Table 1. Specific nuances for each step related to use of audio or video data are included.

Table 1.

Live coding steps.

Live coding
1. Creating semi-structured interview protocol
These questions/answers serve as initial coding schema/themes for the coding process.
This may be recursive in nature and include additional questions as they arise in subsequent interviews.
2. Interviewing study participant(s) and audio/video recording
Video recording allows for visual and audio data to be coded (including visual non-verbals).
Audio allows to code for paralinguistic behavior including tone, rate of speech, and intonation.
3. Watching/listening to the recording for continuity and understanding of the video/audio recording as a whole.
Video can be used to code participants’ non-verbal cues (including head nodding, agreement/disagreement, consensus of participants) as well as verbal speech
4. Note-taking/coding with time stamps during next viewing or listening of the recording
Simultaneous coding while watching/listening to recording based on themes that were developed from the semi-structured interview—including nonverbal, paralinguistic behavior as relevant to the codes
Completing analytical memos by the researchers during this period
Transcribing specific quotes if they help to illustrate specific themes
5. Depending on the theoretical of analytical framework, additional viewings/listening of the recording as needed to complete the coding process

Sample coding

The following includes an example of manual coding with transcription and the use of live coding with video using the same section of the video recording of the focus group for both examples.

The above example (Table 2) provides an approach to live coding in comparison to the initial transcript (Figure 1) coding that resulted in somewhat differing initial codes. The above example of live coding used a similar process to the open coding when using transcripts and similar to the process described by Pennington (2018) when transcribing multimodal documents. The coding team met to discuss emerging themes from the codes, working toward understanding of the themes. Individual and group analytical reflexive notes allowed greater exploration for the reactions and reflections of the researchers, which helped to solidify the selective codes.

Table 2.

Sample coding—video.

Time stamp	Participant quotes	Nonverbals	Initial themes
10:13	I don’t know how much of this was the format intended or how much of this was just a leader, she spent time going through each of our experiences each week and kind of encouraged the group to get to know each other and share their stories a little bit more. I found that really helpful to make it much more personal so it wasn’t just the meditation exercises, it was much more of a support network. She was really good at that.	Participants (x2) nodding	Community building
		Emphasis on really helpful	Weekly check-ins
			Support
10:56	What didn’t go so well for you? (interview question)		Support
11:00	The technology, I mean I know that is sorta of part of it, even just now I tried to be 20 minutes early to this and I was 10 minutes late, just finding the email, getting the link, getting the passcodes to work, it was more often than not I had, it was usually annoying and occasionally prohibitive, I know that is sort of the point, I know it’s better than needing to drive somewhere or something like that but at the same time, if I was like out at dinner, I was doing this while I was pregnant so I could be out the bar and having a nice time and I was having to go to that thing and hustle and I go to that thing and it’s not happening, that’s super disappointing, the technology was sort of a drag	Nodding by all participants	Technology
11:00		Frustration and disappointment	Technology

Figure 1.

Sample coding—transcript.

For example, the identity of both researchers as mothers and how this impacted the lens with which they approached the data and the themes was discussed. The team also made notes about the process of coding in our reflexive notes, including things that we liked and disliked in the process of live coding. One of the underdeveloped, but critical themes that emerged from the focus group data, related to the identity of one of the participants as a woman of color, which may not have come up if the coding had not been done live (visually seeing the woman of color saying it). When reading the transcript, the racial identities of the participants were not clearly identified. The other dimension that live coding offered was being able to see what the participants were saying, which was parallel to how they wanted to be engaged in the group process. For example, participants would join the focus group late or take a step back to console their baby, requiring the group and the space to be flexible to their needs—a positive that the women noted verbally as they described what they liked about the mindfulness groups.

Reflections of the live coding process

The coding team discussed specific themes related to the live coding process and the reflections of the researchers. The team members kept notes about the process of coding to better understand the differences between the live coding and the manual coding process. There were differences in how each coding team member interpreted in the live coding process. Below are the themes and excerpts from the notes:

One researcher found the process of live coding more difficult while the other researcher found it easier:

Coding Researcher 2

Coding without transcripts was difficult. I found myself inclined to make notes on each comment by every participant to be sure I did not miss anything. If I had been watching video with transcripts, I believe it would have been easier to highlight recurring themes without getting lost in the details.

Coding Researcher 1

When coding with transcripts, I often found myself getting lost in the words and having to re-read the transcripts multiple times to get the gist of the content, whereas with the recording I could connect with their stories and could pull out salient themes.

Another theme that emerged from using the process of live coding which made the analysis easier was using thematic analysis:

Although I ended up transcribing the video, I found the process less cumbersome since I was looking for specific themes. I would imagine this would be difficult to do if the structure of the interview or the recordings had been different.

The focus group transcripts were more difficult to follow in text when compared to watching the recordings of the focus groups:

As I read through the transcript, I had a difficult time having a clear sense of the person who was talking from just the words or the names of the participant. However, when I was watching the video I felt like I got to know the person and what they were saying in the context of their reaction to others’ comments. This helped me to code based on the themes that were also emerging for the person.

The themes from exploring the process of live coding suggest some specific benefits and challenges that were observed by both members of the coding team. While one member found it easier to immerse themselves in the data, the other felt that they had to be diligently taking notes while watching the video. Given the nature of the focus groups and the difficulty in managing multiple participants at times talking at once, the coding team found that the video made it easier to code for themes compared to the text data. There were also clear nonverbal interactions with the participants both with each other and their babies that were not noted in the text as it was incongruent (i.e. talking about the difficulty in technology while also cooing at their baby) to what they were talking about. Yet, this theme of connection and community was important to overall research question that would not have been coded using text alone (Latendresse, 2017b). Finally, there appeared to be a personal connection that the coding team was able to make with the participants beyond reading the text found in the transcription.

Discussion

Qualitative research has become increasingly utilized in the fields of social sciences including social work and health research (Taylor and Francis, 2013). Qualitative research includes massive amounts of data, making the analysis a weighty and lengthy process. New technology that assists with the data analysis process is increasingly being used, making qualitative research more user friendly and nuanced (Brown, 2002; Merriam and Tisdell, 2016; Redlich-Amirav and Higginbottom, 2014). Qualitative researchers are likely using some methods similar to live coding described in this article using available digital tools as many have functions to code audio and video data directly; however, little information is available to understand the process. Pennington (2018) includes various ways to analyze digital data that also include video data; nevertheless, traditional methods to coding that use audio and video data from interviews or focus groups still often require transcription as a preliminary step in the process of coding. Yet, arguably, as Packer (2018: 215) states, “certainly what is said is usually recorded and transcribed, but can these kinds of text – spoken and written – really be considered in the same way?” Further, the author elucidates that it is the joint interaction of the interviewer and interviewee that is at the core of data analysis and live coding could possibly offer some of this interaction if the interviewer is primarily coding the video or audio data.

Coding is often a fundamental process of analyzing text and visual data and is often used with interviews and focus groups. Coding primarily involves analyzing texts to generate themes that help to make meaning of the data. The common process for coding involves transcribing audio and video data into text and then conducting the analysis (Saldaña, 2016). As one study found, “traditional methods of transcription run the risk of reducing the impact of the participants’ words by removing them from both the context in which they were collected and the manner in which they were said (Crichton and Childs, 2005).” Live coding as proposed in this paper is an alternate method to coding that may help to deepen the analysis and offer context to the words of the participants. Table 3 briefly describes the benefits and disadvantages of live coding audio/visual data used in this paper compared to coding using transcripts alone:

Table 3.

Benefits and disadvantages of live coding.

Benefits	Disadvantages
Allows way to code non-verbal behavior in the audio or video recordings	Do not get to visualize the participants words which may result in themes that are missed or miscoded
Simultaneously coding allowed for participants intent and context to be realized within the themes	Coding non-verbal behavior (much like verbal behavior) includes cultural nuances making it difficult to have multiple coders agree on coding schema
Focus group audio and videos could lend themselves to the process of live coding, offering richer data analysis than just reading transcripts	Level of detail might be missed when not having access to the written text
The bias associated with transcription is reduced using the voice of the participants	Easier to search for “words” within the transcription versus no way to search within audio video recording

Live coding requires coding of the audio and visual data rather than translating the data to text prior to the analysis. This may eliminate the need for transcription in some instances or live coding could be using in conjunction, addressing some of the difficulties around the transcription process for more depth in the analysis. In reviewing the process of live coding, we found that live coding method allowed for coding of non-verbal content including non-verbal participant agreement, the visual of the participant (and their visible identities), emotion, the emphasis of certain phrases, and other paralinguistic behavior which offered depth and preserved the voice of the participant. Additionally, the context and environment surrounding the responses that the participants provided was value-additive, offering rich data which otherwise would have missed underlying themes that were salient to the research question.

A clear distinction between coding transcripts and live coding was the intimate connection of the codes to the voice of the participants. Seeing and hearing participants while noting their nonverbals offered additional layers to the participant’s text. This provided additional depth to the analysis that was missing from coding of the transcripts alone. Although listening or watching to the audio prior to coding is inherent to the process of immersion in the data, hearing the voice of the participant brings aspects of emotion, intent, and context that offers life that is otherwise lost on paper. Especially, as we considered the many voices in the focus groups, it was evident that the interaction between members in the group would have been lacking resulting in themes that would have been lost through transcript analysis. The nonverbal responses (i.e. head nodding, avoidance of eye contact during a response, focus on their babies) extended the themes beyond what they were saying and what was in the text of the transcription. The text data allow for a focus on the words of the participants, and when transcripts include nonverbal behaviors, these can be coded during the data analysis; however, it is very different to read a nonverbal action versus seeing it simultaneously as the participant is speaking.

Implications

Live coding can be a vehicle to make qualitative research more accessible. The use of audio and video recordings in the process of coding rather than the text only can provide context for things that text often misses. As with any method, the benefits and drawbacks of the new process must be considered. Using video and audio directly offers a way to code for nonverbal occurrences, listen, and see the participant’s voices, and use it to support the verbal content (Chandler et al., 2015). Ideally, directly coding both transcripts and audio/visual may offer the most comprehensive approach; albeit more immersion in the data analysis process. Some of the drawbacks are that codes may be missed or miscoded with the lack of transcription. Additionally, it may not be the best method for some researchers where the visual text in transcriptions helps to ground them. Directly coding audio/video data of focus groups may lend itself to incorporate the intricacies of group dynamics as part of the analysis (Onwuegbuzie et al., 2009).

Live coding could be used within the current technological data analytic resources such as CAQDAS which already include ways to directly code audio and video data. One study found that digital software supported data storage and management and to ensure rigor needed to be combined with manual coding (Maher et al., 2018). Live coding may offer a way to utilize digital software more sophisticatedly beyond data management in the analysis process offering things that are present in manual coding. Even for those that are interested in coding without the use of technology, live coding may offer a way to integrate the non-verbal and paralinguistic interactions into the data analysis process. Focus groups often are difficult to translate into the text, as there are many nuances of having a group interaction. In this case, especially, live coding may be a more attractive and comprehensive method.

Limitations/future directions

This study only considered focus groups that used a semi-structured interview protocol using thematic analysis within a deductive framework which lends itself to specific themes more readily than using an inductive framework (Gläser and Laudel, 2013). For more detailed understanding of the process, it would be helpful to understand the use of live coding with individual interviews using an inductive process through data immersion. Additionally, the data were straightforward and, therefore, were easier to draw out the themes. Thus, it would be important to understand what the process would look like when using data that require developing codes through an inductive process. The comparative process occurred with one researcher coding videos and then coding the transcripts. Therefore, initially, coding the videos informed the coding of the transcripts and likely influenced the process. Another limitation is that transcripts can be de-identified; whereas when using audio and video recordings, the participants are “visible” to the data analysts. However, this is also a benefit where seeing the participants may offer information that otherwise might be missed in the text.

Future research should include understanding live coding in a more inductive process with codes and themes emerging from the data. A comparative model where two teams of researchers code the same data using live coding and traditional methods using transcription may help to better understand the benefits and drawbacks of the live coding process. It would also be helpful to understand the extent to which researchers have a clear stance in their theoretical perspective when they are transcribing data. Further research using this methodology in conjunction with current qualitative data analysis software (such as Nvivo and Atlas.ti) may be helpful to further illuminate the process of qualitative research. Last, as this is a new way of approaching the data analysis, the credibility, transferability, confirmability, and dependability of the live coding process should be considered (Yin, 2016).

Footnotes

Acknowledgement

We thank Dr. Sue Morrow for editing and revising the paper and for feedback that greatly improved the manuscript.

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 author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: University of Utah, College of Nursing.

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