SOLUTION: Qualitative data analysis | My Assignment Tutor

COMMENTARYA hands-on guide to doing content analysisChristen Erlingsson a,⇑, Petra Brysiewicz ba Department of Health and Caring Sciences, Linnaeus University, Kalmar 391 82, Swedenb School of Nursing & Public Health, University of KwaZulu-Natal, Durban 4041, South Africaa r t i c l e i n f oArticle history:Received 21 February 2017Revised 6 May 2017Accepted 4 August 2017Available online 21 August 2017Keywords:Qualitative researchQualitative data analysisContent analysisa b s t r a c tThere is a growing recognition for the important role played by qualitative research and its usefulness inmany fields, including the emergency care context in Africa. Novice qualitative researchers are oftendaunted by the prospect of qualitative data analysis and thus may experience much difficulty in the dataanalysis process. Our objective with this manuscript is to provide a practical hands-on example of qualitative content analysis to aid novice qualitative researchers in their task. 2017 African Federation for Emergency Medicine. Publishing services provided by Elsevier B.V. This isan open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).African relevance Qualitative research is useful to deepen the understanding ofthe human experience. Novice qualitative researchers may benefit from this hands-onguide to content analysis. Practical tips and data analysis templates are provided to assistin the analysis process.IntroductionThere is a growing recognition for the important role played byqualitative research and its usefulness in many fields, includingemergency care research. An increasing number of health researchers are currently opting to use various qualitative researchapproaches in exploring and describing complex phenomena, providing textual accounts of individuals’ ‘‘life worlds”, and givingvoice to vulnerable populations our patients so often represent.Many articles and books are available that describe qualitativeresearch methods and provide overviews of content analysis procedures [1–10]. Some articles include step-by-step directionsintended to clarify content analysis methodology. What we havefound in our teaching experience is that these directions are indeedvery useful. However, qualitative researchers, especially noviceresearchers, often struggle to understand what is happening onand between steps, i.e., how the steps are taken.As research supervisors of postgraduate health professionals,we often meet students who present brilliant ideas for qualitativestudies that have potential to fill current gaps in the literature.Typically, the suggested studies aim to explore human experience.Research questions exploring human experience are expedientlystudied through analysing textual data e.g., collected in individualinterviews, focus groups, documents, or documented participantobservation. When reflecting on the proposed study aim togetherwith the student, we often suggest content analysis methodologyas the best fit for the study and the student, especially the noviceresearcher. The interview data are collected and the content analysis adventure begins. Students soon realise that data based onhuman experiences are complex, multifaceted and often carrymeaning on multiple levels.For many novice researchers, analysing qualitative data is foundto be unexpectedly challenging and time-consuming. As they soondiscover, there is no step-wise analysis process that can be appliedto the data like a pattern cutter at a textile factory. They maybecome extremely annoyed and frustrated during the hands-onenterprise of qualitative content analysis.The novice researcher may lament, ‘‘I’ve read all the methodology but don’t really know how to start and exactly what to do withmy data!” They grapple with qualitative research terms andconcepts, for example; differences between meaning units, codes,categories and themes, and regarding increasing levels of abstraction from raw data to categories or themes. The content analysisadventure may now seem to be a chaotic undertaking. But, life ismessy, complex and utterly fascinating. Experiencing chaos duringhttp://dx.doi.org/10.1016/j.afjem.2017.08.0012211-419X/ 2017 African Federation for Emergency Medicine. Publishing services provided by Elsevier B.V.This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer review under responsibility of African Federation for Emergency Medicine.⇑ Corresponding author.E-mail addresses: christen.erlingsson@lnu.se (C. Erlingsson), brysiewiczp@ukzn.ac.za (P. Brysiewicz).African Journal of Emergency Medicine 7 (2017) 93–99Contents lists available at ScienceDirectAfrican Journal of Emergency Medicinejournal homepage: www.sciencedirect.comanalysis is normal. Good advice for the qualitative researcher is tobe open to the complexity in the data and utilise one’s flow ofcreativity.Inspired primarily by descriptions of ‘‘conventional contentanalysis” in Hsieh and Shannon [3], ‘‘inductive content analysis”in Elo and Kyngäs [5] and ‘‘qualitative content analysis of an interview text” in Graneheim and Lundman [1], we have written thispaper to help the novice qualitative researcher navigate the uncertainty in-between the steps of qualitative content analysis. We willprovide advice and practical tips, as well as data analysis templates, to attempt to ease frustration and hopefully, inspire readersto discover how this exciting methodology contributes to developing a deeper understanding of human experience and our professional contexts.Overview of qualitative content analysisSynopsis of content analysisA common starting point for qualitative content analysis isoften transcribed interview texts. The objective in qualitative content analysis is to systematically transform a large amount of textinto a highly organised and concise summary of key results. Analysis of the raw data from verbatim transcribed interviews to formcategories or themes is a process of further abstraction of data ateach step of the analysis; from the manifest and literal contentto latent meanings (Fig. 1 and Table 1).The initial step is to read and re-read the interviews to get asense of the whole, i.e., to gain a general understanding of whatyour participants are talking about. At this point you may alreadystart to get ideas of what the main points or ideas are that yourparticipants are expressing. Then one needs to start dividing upthe text into smaller parts, namely, into meaning units. One thencondenses these meaning units further. While doing this, you needto ensure that the core meaning is still retained. The next step is tolabel condensed meaning units by formulating codes and thengrouping these codes into categories. Depending on the study’saim and quality of the collected data, one may choose categoriesas the highest level of abstraction for reporting results or you cango further and create themes [1–3,5,8].Higher levels ofabstraconReflects the interpreted,latent meaning of the textOverarching theme The emergency centre through paents’ eyesAlone and cold in chaosLower levels ofabstraconClose to the text andmanifest contentTheme Not a person, just a body in the hecc ECCategory Staff acons and non-aconsCode Le aloneCondensedmeaning unitsPushed to the middle of the room, walkedaway, le meMeaningunit“They pushed me into the middle of theroom and then walked away… they just leme”Fig. 1. Example of analysis leading to higher levels of abstraction; from manifest to latent content.Table 1Glossary of terms as used in this hands-on guide to doing content analysis.*Condensation Condensation is a process of shortening the text while stillpreserving the core meaningCode A code can be thought of as a label; a name that most exactlydescribes what this particular condensed meaning unit isabout. Usually one or two words longCategory A category is formed by grouping together those codes thatare related to each other through their content or context. Inother words, codes are organised into a category when theyare describing different aspects, similarities or differences, ofthe text’s content that belong togetherWhen analysis has led to a plethora of codes, it can be helpfulto first assimilate smaller groups of closely related codes insub-categories. Sub-categories related to each other throughtheir content can then be grouped into categoriesA category answers questions about who, what, when, orwhere? In other words, categories are an expression ofmanifest content, i.e., what is visible and obvious in the dataCategory names are factual and shortTheme A theme can be seen as expressing an underlying meaning,i.e., latent content, found in two or more categories.Themes are expressing data on an interpretative (latent)level. A theme answers questions such as why, how, in whatway, or by what means?A theme is intended to communicate with the reader on bothan intellectual and emotional level. Therefore poetic andmetaphoric language is well suited in theme names toexpress underlying meaningTheme names are very descriptive and include verbs, adverbsand adjectives* More information found in Refs. [1–3,5]94 C. Erlingsson, P. Brysiewicz / African Journal of Emergency Medicine 7 (2017) 93–99Content analysis as a reflective processYou must mould the clay of the data, tapping into your intuitionwhile maintaining a reflective understanding of how your ownprevious knowledge is influencing your analysis, i.e., your preunderstanding. In qualitative methodology, it is imperative to vigilantly maintain an awareness of one’s pre-understanding so thatthis does not influence analysis and/or results. This is the difficultbalancing task of keeping a firm grip on one’s assumptions, opinions, and personal beliefs, and not letting them unconsciously steeryour analysis process while simultaneously, and knowingly, utilising one’s pre-understanding to facilitate a deeper understanding ofthe data.Content analysis, as in all qualitative analysis, is a reflective process. There is no ‘‘step 1, 2, 3, done!” linear progression in the analysis. This means that identifying and condensing meaning units,coding, and categorising are not one-time events. It is a continuousprocess of coding and categorising then returning to the raw datato reflect on your initial analysis. Are you still satisfied with thelength of meaning units? Do the condensed meaning units andcodes still ‘‘fit” with each other? Do the codes still fit into this particular category? Typically, a fair amount of adjusting is neededafter the first analysis endeavour. For example: a meaning unitmight need to be split into two meaning units in order to capturean additional core meaning; a code modified to more closely matchthe core meaning of the condensed meaning unit; or a categoryname tweaked to most accurately describe the included codes. Inother words, analysis is a flexible reflective process of workingand re-working your data that reveals connections and relationships. Once condensed meaning units are coded it is easier to geta bigger picture and see patterns in your codes and organise codesin categories.Content analysis exerciseThe synopsis above is representative of analysis descriptions inmany content analysis articles. Although correct, such methoddescriptions still do not provide much support for the noviceresearcher during the actual analysis process. Aspiring to provideguidance and direction to support the novice, a practical exampleof doing the actual work of content analysis is provided in the following sections. This practical example is based on a transcribedinterview excerpt that was part of a study that aimed to explorepatients’ experiences of being admitted into the emergency centre(Fig. 2).This content analysis exercise provides instructions, tips, andadvice to support the content analysis novice in a) familiarisingoneself with the data and the hermeneutic spiral, b) dividing upthe text into meaning units and subsequently condensing thesemeaning units, c) formulating codes, and d) developing categoriesand themes.Familiarising oneself with the data and the hermeneutic spiralAn important initial phase in the data analysis process is to readand re-read the transcribed interview while keeping your aim inFig. 2. Excerpt from interview text exploring ‘‘Patient’s experience of being admitted into the emergency centre”C. Erlingsson, P. Brysiewicz / African Journal of Emergency Medicine 7 (2017) 93–99 95focus. Write down your initial impressions. Embrace your intuition. What is the text talking about? What stands out? How didyou react while reading the text? What message did the text leaveyou with? In this analysis phase, you are gaining a sense of the textas a whole.You may ask why this is important. During analysis, you will bebreaking down the whole text into smaller parts. Returning to yournotes with your initial impressions will help you see if your ‘‘parts”analysis is matching up with your first impressions of the ‘‘whole”text. Are your initial impressions visible in your analysis of theparts? Perhaps you need to go back and check for different perspectives. This is what is referred to as the hermeneutic spiral orhermeneutic circle. It is the process of comparing the parts to thewhole to determine whether impressions of the whole verify theanalysis of the parts in all phases of analysis. Each part shouldreflect the whole and the whole should be reflected in each part.This concept will become clearer as you start working with yourdata.Dividing up the text into meaning units and condensing meaning unitsYou have now read the interview a number of times. Keepingyour research aim and question clearly in focus, divide up the textinto meaning units. Located meaning units are then condensed further while keeping the central meaning intact (Table 2). The condensation should be a shortened version of the same text thatstill conveys the essential message of the meaning unit. Sometimesthe meaning unit is already so compact that no further condensation is required. Some content analysis sources warn researchersagainst short meaning units, claiming that this can lead to fragmentation [1]. However, our personal experience as researchsupervisors has shown us that a greater problem for the novice isbasing analysis on meaning units that are too large and includemany meanings which are then lost in the condensation process.Formulating codesThe next step is to develop codes that are descriptive labels forthe condensed meaning units (Table 3). Codes concisely describethe condensed meaning unit and are tools to help researchersreflect on the data in new ways. Codes make it easier to identifyconnections between meaning units. At this stage of analysis youare still keeping very close to your data with very limited interpretation of content. You may adjust, re-do, re-think, and re-code untilyou get to the point where you are satisfied that your choices arereasonable. Just as in the initial phase of getting to know your dataas a whole, it is also good to write notes during coding on yourimpressions and reactions to the text.Developing categories and themesThe next step is to sort codes into categories that answer thequestions who, what, when or where? One does this by comparingcodes and appraising them to determine which codes seem tobelong together, thereby forming a category. In other words, a category consists of codes that appear to deal with the same issue, i.e.,manifest content visible in the data with limited interpretation onTable 2Suggestion for how the exemplar interview text can be divided into meaning units and condensed meaning units (condensations are in parentheses).Meaning units (Condensations)– Well, ok, where to start, that was a bad day in my life (It was a bad day in my life)– And it started so much the same as any other day. Right up until I was in that car crash! (Ordinary day until the crash)– I still have nightmares about the sound of the other car and the lady screaming (Nightmares about sounds of the crash)– I can’t get the sound out of my head! (Can’t get the sound out of my head)– it is a crazy place there. Do you know. . .do you work there? (Emergency Centre is a crazy place)– Well the people in the ambulance, when they had me in the ambulance they were looking worried, they kept telling me ‘‘there was lots of blood here” (Ambulance stafflooked worried about all the blood)– I really remember that. I thought, ‘‘Well there is not much I can do” (Thinking that I couldn’t do anything about it)– Anyway, they seemed to want to get me into the EC in a real hurry. Then pushed my trolley in fast. (Ambulance staff were in a great hurry to get the trolley into EC)– I was feeling very cold. I think my legs were shaking. (I feel cold and my legs are shaking)– I think they had cut off my jeans. It was very uncomfortable, (Jeans cut off and very uncomfortable)– I wasn’t sure if the blanket covered me. I tried to grab the blanket with my hand. (Tried to grab the blanket to cover me)– They must have given me something, maybe in that drip thing (Must have been given something in a drip)– because I remember thinking that I should be in pain. . .. my legs must be sore. . . they were jammed in the car . . .but I really can’t remember feeling it (Thinking Ishould be in pain but can’t remember feeling legs jammed in the car)– just remember being cold, shaky (Being cold and shaky)– feeling very alone (Feeling very alone)– just saw everything moving past me (Only saw things moving past me)– I really wished my sister was there. She always seems to know what to do. She doesn’t panic, (I wanted my sister who knows what to do and doesn’t panic)– But there was no one. (There was no one)– No one spoke to me. (No one spoke to me)– I wondered if I was invisible. (Was I invisible)– They pushed me into a big room and there were lots of people there. It looked so busy, lots of noise, phones ringing, people talking loudly (Placed in a big, busy, noisyroom)– And I remember thinking that my sister wouldn’t know how to find me (Thinking my sister wouldn’t find me)– I tried to tell the ambulance guy that I needed him to please call my sister (Tried to tell ambulance guy I needed him to call my sister)– . . . but I had a thing on my face – for air they said before– so no one heard me, (with this thing on my face no one heard me)– No one seemed to be looking at my face. (No one looked at my face)– They pushed me into the middle of the room and then walked away. They just left me (Pushed me to the middle of the room, walked away, left me)– And I am not sure what everyone was doing (I didn’t know what they were doing)– They seemed to be rushing around (They were rushing about)– . . . but no one spoke to me. (No one spoke to me)– Suddenly someone grabbed my leg, (Suddenly someone grabbed my leg)– I got such a fright (I got a fright)– they didn’t say anything to me. . . (Saying nothing to me)– just poked my leg. (They poked my leg)– I remember screaming. (I screamed)– I remember that pain! (I remember the pain)96 C. Erlingsson, P. Brysiewicz / African Journal of Emergency Medicine 7 (2017) 93–99the part of the researcher. Category names are most often shortand factual sounding.In data that is rich with latent meaning, analysis can be carriedon to create themes. In our practical example, we have continuedthe process of abstracting data to a higher level, from category totheme level, and developed three themes as well as an overarchingtheme (Table 4). Themes express underlying meaning, i.e., latentcontent, and are formed by grouping two or more categoriestogether. Themes are answering questions such as why, how, inwhat way or by what means? Therefore, theme names includeverbs, adverbs and adjectives and are very descriptive or evenpoetic.Some reflections and helpful tipsUnderstand your pre-understandingsWhile conducting qualitative research, it is paramount that theresearcher maintains a vigilance of non-bias during analysis. Inother words, did you remain aware of your pre-understandings,i.e., your own personal assumptions, professional background,and previous experiences and knowledge? For example, did youzero in on particular aspects of the interview on account of yourprofession (as an emergency doctor, emergency nurse, prehospital professional, etc.)? Did you assume the patient’s gender?Did your assumptions affect your analysis? How about aspects ofculpability; did you assume that this patient was at fault or thatthis patient was a victim in the crash? Did this affect how you analysed the text?Staying aware of one’s pre-understandings is exactly as difficultas it sounds. But, it is possible and it is requisite. Focus on puttingyourself and your pre-understandings in a holding pattern whileyou approach your data with an openness and expectation of finding new perspectives. That is the key: expect the new and be prepared to be surprised. If something in your data feels unusual, isdifferent from what you know, atypical, or even odd – don’t bypass it as ‘‘wrong”. Your reactions and intuitive responses are letting you know that here is something to pay extra attention to,besides the more comfortable condensing and coding of moreeasily recognisable meaning units.Use your intuitionIntuition is a great asset in qualitative analysis and not to bedismissed as ‘‘unscientific”. Intuition results from tacit knowledge.Just as tacit knowledge is a hallmark of great clinicians [11,12]; it isalso an invaluable tool in analysis work [13]. Literally, take note ofyour gut reactions and intuitive guidance and remember to writethese down! These notes often form a framework of possible avenues for further analysis and are especially helpful as you lift theanalysis to higher levels of abstraction; from meaning units to condensed meaning units, to codes, to categories and then to the highest level of abstraction in content analysis, themes.Aspects of coding and categorising hard to place dataAll too often, the novice gets overwhelmed by interview material that deals with the general subject matter of the interview, butdoesn’t seem to answer the research question. Don’t be too quickto consider such text as off topic or dross [6]. There is often datathat, although not seeming to match the study aim precisely, is stillimportant for illuminating the problem area. This can be seen inour practical example about exploring patients’ experiences ofbeing admitted into the emergency centre. Initially the participantis describing the accident itself. While not directly answering theresearch question, the description is important for understandingthe context of the experience of being admitted into the emergencycentre. It is very common that participants will ‘‘begin at the beginning” and prologue their narratives in order to create a context thatsets the scene. This type of contextual data is vital for gaining adeepened understanding of participants’ experiences.In our practical example, the participant begins by describingthe crash and the rescue, i.e., experiences leading up to and priorto admission to the emergency centre. That is why we have chosenin our analysis to code the condensed meaning unit ‘‘Ambulancestaff looked worried about all the blood” as ‘‘In the ambulance”and place it in the category ‘‘Reliving the rescue”. We did notchoose to include this meaning unit in the categories specificallyabout admission to the emergency centre itself. Do you agree withour coding choice? Would you have chosen differently?Another common problem for the novice is deciding how tocode condensed meaning units when the unit can be labelled inseveral different ways. At this point researchers usually groanand wish they had thought to ask one of those classic follow-upquestions like ‘‘Can you tell me a little bit more about that?” Wehave examples of two such coding conundrums in the exemplar,as can be seen in Table 3 (codes we conferred on) and Table 4(codes we reached consensus on). Do you agree with our choicesor would you have chosen different codes? Our best advice is toTable 3Suggestions for coding of condensed meaning units.Meaning units condensations Codes It was a bad day in my lifeThe crashOrdinary day until the crashThe crashNightmares about the sounds of the crashCan’t get the sound out of my headEmergency Centre is a crazy placeThe crashThe crashEmergency Centreis crazyIn the ambulance?*Ambulance staff looked worried about all the bloodI couldn’t do anything about it Ambulance staff were in a great hurry to get the trolleyinto ECStaff in a hurry I feel cold and my legs are shakingCold and shakyJeans cut off and very uncomfortableFeeling exposedTried to grab the blanket to cover meFeeling exposedMust have been given something in a dripIn the ambulance Thinking I should be in pain but can’t remember feelinglegs jammed in the carIn the ambulanceBeing cold and shaky Cold and shakyFeeling very alone Feeling aloneOnly saw things moving past me Emergency Centreis busyI wanted my sister who knows what to do and doesn’tpanicWanting support There was no oneFeeling aloneNo one spoke to meNot spoken toWas I invisibleA big, busy, noisy roomFeeling invisibleEmergency Centreis noisy?**Thinking my sister wouldn’t find me Tried to tell ambulance guy I needed him to call mysisterWanting help With this thing on my face no one heard meNot heardNo one looked at my faceNot looked at Pushed me to the middle of the room, walked away, leftmeLeft alone I didn’t know what they were doingThey were rushing aboutUnsureStaff in a hurryNo one spoke to meNot spoken toSuddenly someone grabbed my legStaff actionsI got a frightFrightenedSaying nothing to meNot spoken toThey poked my legStaff actionsI screamedPainI remember the painPain * Feeling helpless? Resigned, Powerless? ‘‘In god’s hands”? What do you think?** Worried? Feeling lost? Distraught? What do you think?C. Erlingsson, P. Brysiewicz / African Journal of Emergency Medicine 7 (2017) 93–99 97go back to your impressions of the whole and lean into your intuition when choosing codes that are most reasonable and best fityour data.A typical problem area during categorisation, especially for thenovice researcher, is overlap between content in more than oneinitial category, i.e., codes included in one category also seem tobe a fit for another category. Overlap between initial categories isvery likely an indication that the jump from code to categorywas too big, a problem not uncommon when the data is voluminous and/or very complex. In such cases, it can be helpful to firstsort codes into narrower categories, so-called subcategories. Subcategories can then be reviewed for possibilities of further aggregation into categories. In the case of a problematic coding, it isadvantageous to return to the meaning unit and check if the meaning unit itself fits the category or if you need to reconsider yourpreliminary coding.It is not uncommon to be faced by thorny problems such as theseduring coding and categorisation. Here we would like to reiteratehow valuable it is to have fellow researchers with whom you candiscuss and reflect together with, in order to reach consensus onthe best way forward in your data analysis. It is really advantageousto compare your analysis with meaning units, condensations, coding and categorisations done by another researcher on the sametext. Have you identified the same meaning units? Do you agreeon coding? See similar patterns in the data? Concur on categories?Sometimes referred to as ‘‘researcher triangulation,” this is actuallya key element in qualitative analysis and an important componentwhen striving to ensure trustworthiness in your study [14]. Qualitative research is about seeking out variations and not controllingvariables, as in quantitative research. Collaborating with others during analysis lets you tap into multiple perspectives and often makesit easier to see variations in the data, thereby enhancing the qualityof your results as well as contributing to the rigor of your study. It isimportant to note that it is not necessary to force consensus in thefindings but one can embrace these variations in interpretationand use that to capture the richness in the data.Yet there are times when neither openness, pre-understanding,intuition, nor researcher triangulation does the job; for example,when analysing an interview and one is simply confused on howto code certain meaning units. At such times, there are a varietyof options. A good starting place is to re-read all the interviewsthrough the lens of this specific issue and actively search for othersimilar types of meaning units you might have missed. Anotherway to handle this is to conduct further interviews with specificTable 4Suggestion for organisation of coded meaning units into categories and themes.Overarching theme: THE EMERGENCY CENTRE THROUGH PATIENTS’ EYES – ALONE AND COLD IN CHAOSTheme: Reliving the pre-hospital experienceCondensations Codes CategoriesIt was a bad day in my life The crash Reliving the crashOrdinary day until the crash The crashNightmares about the sounds of the crash The crashCan’t get the sound out of my head The crashAmbulance staff looked worried about all the blood In the ambulance Reliving the rescueMust have been givensomething in a dripIn the ambulanceThinking I should be in pain but can’t rememberfeeling legs jammed in the carIn the ambulanceTheme: Not a person, just a body in the hectic ECCondensations Codes CategoriesEC is a crazy place Emergency Centre iscrazyEmergency Centre is a crazy,noisy, environmentOnly saw things moving past me Emergency Centre isbusyA big, busy noisy room Emergency Centre isnoisyAmbulance staff were in a great hurry to get the trolley into EC Staff in a hurry Staff actions and non-actionsThey were rushing about Staff in a hurryPushed me to the middle of the room, walked away, left me Left aloneNo one spoke to me Not spoken toNo one spoke to me Not spoken toSaying nothing to me Not spoken toSuddenly someone grabbed my leg Staff actionsThey poked my leg Staff actionsNo one looked at my face Not looked atWith this thing on my face no one heard me Not heardI wanted my sister who knows what to do and doesn’t panic Wanting support Unmet needsTried to tell ambulance guy I needed him to call my sister Wanting helpTheme: Invisible and alone inside the pain of a broken bodyCondensations Codes CategoriesI feel cold and my legs are shaking Cold and shaky Physical responsesBeing cold and shaky Cold and shakyI remember the pain PainI screamed PainI couldn’t do anything about it Feeling helpless Emotional responsesPants cut off and very uncomfortable Feeling exposedTried to grab the blanket to cover me Feeling exposedWas I invisible Feeling invisibleThere was no one, Feeling aloneFeeling very alone Feeling aloneI didn’t know what they were doing UnsureThinking my sister wouldn’t find me Feeling lostI got a fright Frightened98 C. Erlingsson, P. Brysiewicz / African Journal of Emergency Medicine 7 (2017) 93–99queries that hopefully shed light on the issue. A third option is tohave a follow-up interview with the same person and ask themto explain.Additional tipsIt is important to remember that in a typical project there areseveral interviews to analyse. Codes found in a single interviewserve as a starting point as you then work through the remaininginterviews coding all material. Form your categories and themeswhen all project interviews have been coded.When submitting an article with your study results, it is a goodidea to create a table or figure providing a few key examples ofhow you progressed from the raw data of meaning units, to condensed meaning units, coding, categorisation, and, if included,themes. Providing such a table or figure supports the rigor of yourstudy [1] and is an element greatly appreciated by reviewers andresearch consumers.During the analysis process, it can be advantageous to writedown your research aim and questions on a sheet of paper thatyou keep nearby as you work. Frequently referring to your aimcan help you keep focused and on track during analysis. Many findit helpful to colour code their transcriptions and write notes in themargins.Having access to qualitative analysis software can be greatlyhelpful in organising and retrieving analysed data. Just remember,a computer does not analyse the data. As Jennings [15] has stated,‘‘. . . it is ‘peopleware,’ not software, that analyses.” A major drawback is that qualitative analysis software can be prohibitivelyexpensive. One way forward is to use table templates such as wehave used in this article. (Three analysis templates, Templates A,B, and C, are provided as supplementary online material). Additionally, the ‘‘find” function in word processing programmes such asMicrosoft Word (Redmond, WA USA) facilitates locating key words,e.g., in transcribed interviews, meaning units, and codes.Lessons learnt/key pointsFrom our experience with content analysis we have learnt anumber of important lessons that may be useful for the noviceresearcher. They are: A method description is a guideline supporting analysis andtrustworthiness. Don’t get caught up too rigidly following steps.Reflexivity and flexibility are just as important. Remember thata method description is a tool helping you in the process ofmaking sense of your data by reducing a large amount of textto distil key results. It is important to maintain a vigilant awareness of one’s ownpre-understandings in order to avoid bias during analysis andin results. Use and trust your own intuition during the analysis process. If possible, discuss and reflect together with other researcherswho have analysed the same data. Be open and receptive tonew perspectives. Understand that it is going to take time. Even if you are quiteexperienced, each set of data is different and all require timeto analyse. Don’t expect to have all the data analysis done overa weekend. It may take weeks. You need time to think, reflectand then review your analysis. Keep reminding yourself how excited you have felt about thisarea of research and how interesting it is. Embrace it withenthusiasm! Let it be chaotic – have faith that some sense will start to surface. Don’t be afraid and think you will never get to the end –you will. . . eventually!Appendix A. Supplementary dataSupplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.afjem.2017.08.001.References[1] Graneheim UH, Lundman B. Qualitative content analysis in nursing research:concepts, procedures, and measures to achieve trustworthiness. Nurse EducToday 2004;24:105–12.[2] Mayring P. Qualitative content analysis. 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