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Jaquelina Hewitt-Taylor RGN,RSCN, BA(Hons), PhD, is SeniorLecturer, Distance LearningCentre, South BankUniversity, London.Email: [email protected]

july 4/vol15/no42/2001 nursing standard 39

art&scienceresearch methodsnursing standard: clinical research education

THE AIM OF qualitative research is to portraythe reality of the area under investigation,and to enhance understanding of the situa-tion and the meanings and values attributed tothis by individuals; it does not involve the quantifi-cation of facts (Rose 1994). Qualitative methodsemphasise the value of individual experiencesand views, as encountered in real-life situations.This type of investigation is often useful innursing, as many issues concern the quality of

the lived experience of individuals, which cannotbe reduced to numerical values using statisticalanalysis. Sometimes a mixed methodology mightbe adopted, with elements of qualitative andquantitative enquiry being included in a study.

The nature of qualitative enquiry means thatvolumes of rich, deep data are produced, oftenfrom a variety of sources. While not seeking toreduce data to statistical evidence, qualitativedata nevertheless requires systematic analysis.Given the volume of data produced, the practi-calities of analysing, co-ordinating and ordering

data into a form from which conclusions can bedrawn and recommendations made, can appearoverwhelming. In the qualitative research para-digm, a variety of data analysis procedures arecommonly used (Polit and Hungler 1993). Thisarticle describes the use of constant comparativeanalysis, a method of analysing qualitative datawhere the information gathered is coded intoemergent themes or codes. The data is con-stantly revisited after initial coding, until it isclear that no new themes are emerging. It canbe used in a study with a single method of datacollection, or in situations where multiple datacollection methods have been used.

The study used to illustrate the process ofdata analysis explored the use of self-directedlearning (SDL) in paediatric intensive care nurseeducation (Hewitt-Taylor 2000). It involved a six-

month case study of a paediatric intensive carecourse (ENB 415), using documentary analysis,repeated interviews with teachers and students,observation of course processes and selectedlessons, and student learning diaries. The studyalso included a survey of seven centres offeringthe course: this involved interviews with teachers,focus groups with students and a survey of themanagers of all paediatric intensive care units inEngland, using postal questionnaires. A field diarywas used to record additional data and personalreflections.

All qualitative data analysis methods involvecoding data into themes, then categories, toform conclusions (Jasper 1994); this study usedconstant comparative analysis (Benton 1991,

Morgan 1993). All notes from the analysis of thecourse documents, interview transcripts, obser-vation notes, lesson transcripts, learning diarysummaries, questionnaire transcripts and addi-tional notes from the field diary, were coded.The coding process was carried out by readingeach of these documents and attributing a codeto sentences, paragraphs or sections. These codesrepresented a theme or idea with which each partof the data was associated. For example, the codenursing and self-directed learning was attributedto data that suggested there might be issues in

self-directed learning pertaining specifically tonursing. Sections of transcripts were given nocode, one code or more than one code.

The codes were written on hard copies of eachdocument next to the related section. The codesand their definitions were recorded in a separatefile. For example:I Code nursing and self-directed learning.I Definition any reference to, or indication

that there might be issues relating to, self-directed learning which is specific to nursing.

I Abbreviation NSDL.A separate file was used to ensure that the use ofeach code remained consistent and to establish aclear decision trail that could be used by auditorsor future researchers. During data coding, noteswere made about how decisions had beenreached, how the coding process had been

Coding data

Use of constant comparative

analysis in qualitative researchHewitt-Taylor J (2001) Use of constant comparative analysis in qualitative research.Nursing Standard . 15, 42, 39-42. Date of acceptance: March 19 2001.

This article describes the application ofconstant comparative analysis, which is onemethod that can be used to analysequalitative data. The need for data analysisto be congruent with the overall researchdesign is highlighted.

Summary

I Research methods

These key words are basedon subject headings from theBritish Nursing Index. Thisarticle has been subject todouble-blind review.

Key words

For related articles visit ouronline archive at:www.nursing-standard.co.ukand search using the keywords below.

Online archive

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conducted, and any specific queries raised.Data analysis was inductive, as the study

sought to promote understanding of individualperceptions, not prove a preconceived theory.Codes were, therefore, generated from the

data, rather than predetermined. Although liter-ature-based codes can provide a useful tool,they can impede the development of new ideas(Strauss and Corbin 1990). Having coded thefirst transcript, each subsequent reading of thisand other transcripts was carried out with this inmind. New codes were added as necessary.

After coding the hard copy of each document,the copy was then highlighted, cut and pasted.Each coded section was put onto a new windowand stored on a computer file with the title code.The name of the participant whose interview thecode pertained to, and the line numbers fromthe transcript, were included on each codedsection. It could then be traced to the original toprovide further contextual details that mightbecome necessary as data analysis proceeded.These were then electronically stored in a filewith the name of the code. This was an efficientway to transfer coded segments into a storagearea, with minimum retyping or rewriting. Onehard copy of each coded transcript was retained,in addition to the electronic copy. After finalcoding was complete, code files were printedand stored in files labelled with each code name.

The quality of data analysis depends onrepeated, systematic searching of the data(Hammersley 1981). In an attempt to achievethis, repeated coding was performed to reviewinterpretations, in the light of new data gath-ered and as new codes were generated, until nonew insights were being gleaned (Riley 1990).Established coded sections were compared withother similarly coded segments to ensure consis-tency of application, as well as adherence to thedefinition of the code (Strauss and Corbin1990). Where events or conversations had been

recorded in more than one of the methods used(for example, in observation and interviews),both transcripts were reviewed together afterinitial coding. On some occasions, events frominterviews, observations, or learning diaryentries in the field diary had also been recorded.Then diary entries were reviewed to check if therewas any evidence of extraneous circumstancesinfluencing the researchers interpretation ofevents, or impinging on the event being recorded,to review any other interpretations that wereperceived at the time.

Data collection and analysis are interwoven inqualitative research. Some authors suggest thatthey should proceed together, and conceptdevelopment should be examined in subsequentencounters with the study participants (Belgraveand Smith 1995, MacKenzie 1994). Data should

also be analysed as promptly as possible aftercollection so that qualitative elements of theencounter recorded in the data can be recalledas accurately as possible (Carey 1995). This,combined with the recording of additional notes

in a research journal or diary, ensures that qual-itative data analysis is as rich and detailed aspossible. The process of data analysis was,therefore, commenced before completing thefieldwork, with preliminary analysis performedin a week of the events recorded.

Once coding was completed, the codes thathad common elements were merged to formcategories (Strauss and Corbin 1990). Thecoded sections of data were placed in cate-gories in the data collection methods used. Thiswas performed electronically; files were createdfor each category, containing copies of thecodes that had been merged to form the cate-gory. The definitions of the categories and thecodes placed in these were recorded in the sameway as codes. Some codes were placed inmore than one category. The categorised datawere then printed and stored manually in fileswith the name of each category.

The categories derived from each data collec-tion method were then clustered around eachresearch question they contributed to answering.A list was complied of categories that related toeach research question, and some categories

were used to address more than one question.Once all the research questions had been allot-ted input from the categories, the informationpertaining to each question was examined andreviewed to compile a report. The findings werefinally checked against the diary entries to identifywhether the researchers views recorded before orduring the study had unduly influenced interpre-tation of the data gathered.

Boxes 1 and 2 illustrate a selection of datafrom one data collection method and how itwas broken down into codes, categories and

answers to each research question. Each datacollection method was analysed, coded, andcategorised in this manner.

The interpretation of the responses and emer-gent findings were discussed with the case studyparticipants. Nolan and Behi (1995) suggest thatin qualitative research, the findings should bepresented to participants and their viewsexplored. Others suggest that this should also beapplied to qualitative data analysis (Silverman1993, Wellington 1996). The negotiation ofoutcomes in discussing the emergent findingswith participants was considered congruent withthe equality of power and mutual respect of SDL,making the method of analysis in one respect

Validation by respondents

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congruent with the area studied. However, thisprocedure does not fully validate the findings,and might only mean that the interpretationgiven is acceptable to respondents (Silverman1993). Before discussing the interpretation of

data with participants, it was necessary to decidehow disagreement over interpretations would behandled. Although achieving a balance of poweris important, respondents should not be giventoo much power in relation to defining theresearch interpretations (Riley 1990). Theresearcher felt that respondents might disagreewith the conclusions reached, but that they shouldbe able to recognise the descriptions in the studyas accurate portrayals of events (Fetterman 1989).

Previous interview data, findings from observa-tions, and learning diary entries were explored atsubsequent interviews, and there were no sig-nificant differences of opinion concerning thefindings. However, some concerns wereexpressed over the extent to which one of thestudents agreed with the emergent findings. Ontalking to the student about how the issues hadbeen, she said that she agreed with the inter-pretations, but the researcher was not entirelyconvinced that she did. She might have agreed,but it might be that she did not want to disagreewith the researcher, which would reflect her gen-eral disinclination to disagree with teaching staff.

This type of problem is relevant to any research

where power issues might be perceived to existbetween individuals involved in the study, andmight affect their inclination to disagree withinterpretations, for example, in a nurse-client, ora teacher-student relationship. This type of prob-lem is recognised in the literature (Silverman1993), and indicates that member checks are notnecessarily adequate to achieve complete trustwor-thiness in qualitative research. However, they docontribute to the trustworthiness of the research.

During focus group interviews with students andinterviews with teachers in the survey, points

were summarised as the interviews progressedto promote accuracy and clarify the emergentinterpretations of the participants views (Carey1995).

Data analysis forms part of the research methodsused in an enquiry, and should, therefore, beconsistent with the philosophical underpinningof the study. While placing a method of analysisinto the qualitative or quantitative paradigm isrelatively straightforward, ensuring that the dataanalysis method is congruent with the more subtleelements of the study is sometimes less clear.

Qualitative analysis concerns words not num-bers, and exclusive counting of the frequencywith which codes occurred, or opinions

expressed, would diminish the essence of quali-tative data since its most important element isgenerating precise and in-depth meanings(Morgan 1993). It has been suggested thatcounting how often codes occur is helpful in

clarifying whether reality is in accordance withthe overall impressions gained by the researcher(Morgan 1993, Polit and Hungler 1993,Silverman 1993). However, this view is disputed,as it is possible that numbers alone will becomethe focus, with the loss of subtle nuances ofmeaning and individual views, which are thestrength of qualitative research (Morse 1995). Ingroup processes, not all participants will respondto all questions or be present in all situations,making counting the frequency of codes mean-ingless (Saint Germain et al 1993).

In qualitative research, there is debate concerningthe most appropriate way to establish the qualityof research. Given this debate, the philosophicalassumptions that underpin the research designand the subsequent evaluation criteria shouldbe determined at the outset of the study. Theresearcher had set out to demonstrate that thestudy findings were trustworthy in terms ofdependability and confirmability, credibility andtransferability (Lincoln and Guba 1985). Indeciding on the method of data analysis to beused, it was, therefore, important to ensure thatthe data analysis methods would embrace these

criteria.One criterion used for establishing the con-

firmability of research is the establishment of anaudit trail (Lincoln and Guba 1985). This isintended to allow other individuals to under-stand and evaluate how the data was coded andcategorised, why data was placed into thesecodes and categories, and how these wereclustered to answer the research questions. Inestablishing credibility, analysis proceduresincluded triangulation of data by comparinginterpretations and recordings, and data collec-

tion methods. Member checks added to thecredibility criteria, albeit with an acknowledgmentthat these have their own inherent problems. Oncoding and categorising the data, it is importantnot to lose contextual and descriptive elementsof the data, which add to the transferability ofthe research. This was augmented by ensuringthat data, which were placed into categories,could easily be traced to the original transcript,to review any additional contextual data.

In qualitative data analysis, the main focus is noton quantification of facts, but rather on identi-fying the meanings and values attributed byindividuals in real-life situations, with idiosyn-cratic and personal views forming an important

Conclusion

Methods of analysis

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Research question 1: What do nurse teachers on the ENB 415 course understand by the term self-directed learning?

Categories: Learning defined, not self-directed learning, preparation for self-directed learning, self-directed learning or developing self-directedlearning, what is self-directed learning?

Research question 2: What are the views of nurse teachers on the ENB 415 course concerning the use of self-directed learning?

Categories: Assessment, content, elements of self-directed learning, factors affecting self-directed learning, group issues, nursing issues and self-directed learning, objectives, organisational issues, practice, preferred teaching and learning styles, preparation for self-directed learning, studentability to be self-directed, subjects, teachers beliefs about self-directed learning, teaching methods, teachers role, teacher/student relationship, whystudents attend?

Research question 3: What do students on the ENB 415 course understand by the term self-directed learning?

Categories: Preparation for self-directed learning

Research question 4: What are the views of students on the ENB 415 course concerning the use of self-directed learning?Categories: Preferred teaching and learning styles, preparation for self-directed learning, student evaluation, student views, teacher/studentrelationship, why students attend?

Research question 5: What are the views of purchasers of the ENB 415 course concerning teaching and learning strategies used on the ENB 415course?

Categories used: Employment, nursing issues and self-directed learning, practice

Box 1. A selection of data from interviews with nurse teachers

Box 2. Category clustering

Note: Codes are only shown for Categories 1-8, but they were allocated in a similar manner for Categories 9-25.

Category 1:AssessmentCodes:AssessmentEntrance criteriaFormative assessmentPeer assessmentSelectionSelf-assessmentSummative assessmentValidation /Verification

Category 2:ContentCodes:Concerns over coveringcontentContentCurriculumObligation to covercontentTimetables

Category 3:Elements of self-directed learningCodes:Active participationBuilding on experienceFlexibilityGround rulesIndividual learning stylesIndividual needsLearning contractsLearning from experienceNegotiationPacePersonal learningPractitioners experience

Previous experienceRelevanceStudent-centred learningStudent choiceStudent controlStudent led

Category 4:EmploymentCodes:Employment issues andself-directed learningManagers expectations

Category 5:Factors affecting self-directedlearningCodes:Assumptions regardingstudent needsAttendanceCultureDiffering teacherperceptionsFactors affectingself-directed learningLearning resourcesObligation to useself-directed learningResourcesTeachers ability to beself-directedTeacher expectationsTime factors affectingself-directed learning

Category 6:Group issues

Codes:CompetitivenessGroup dynamicsGroup needsGroup sizePeer learningPeer support

Category 7:Learning definedCodes:Nature of knowledgeSkill acquisitionWhat is learning

Category 8:Not self-directed learningCodes:BehaviourismPrescriptive

Category 9:

Nursing issues and self-directedlearning

Category 10:Objectives

Category 11:Organisational Issues

Category 12:Practice

Category 13:Preferred teaching and learningstyles

Category 14:Preparation for self-directedlearning

Category 15:Self-directed learning

Category 16:Student ability to be self-directed

Category 17:Student evaluation

Category 18:Student views

Category 19:Subjects

Category 20:Teaching methods

Category 21:Teachers role

Category 22:Teacher/student relationship

Category 23:Teachers views of self-directedlearning

Category 24:What is self-directed learning?

Category 25:Why students attend

part of the overall picture. However, there is aneed for thorough and systematic analysis of theinformation generated by these processes. It isimportant to consider how data will be analysedat the design stage of any research, to ensurethat the analysis procedures proposed are inkeeping with the overall philosophy, and fallwithin the evaluative criteria of the study.Successful analysis and presentation of quali-tative data requires a systematic and orderedapproach so that complex data that emerge

from a variety of sources can be collated andpresented in a manageable form. Constantcomparative analysis is one method that can beused to identify broad themes and patterns,or categories that emerge from qualitativeresearch studies. In these categories, theprecise nature of each individuals view canbe captured and recalled and data can bepresented in a logical sequence in relationto the research questions addressed in thestudy

Saint Germain M et al (1993) Survey andfocus groups in health research witholder hispanic women. QualitativeHealth Research . 3, 3, 341-367.

Silverman D (1993) InterpretingQualitative Data . London, Sage.

Strauss A, Corbin J (1990) Basics of

Qualitative Research: Grounded Theory Procedures and Techniques .London, Sage.

Wellington J (1996) Methods and Issuesin Educational Research . Sheffield,Sheffield University Division ofEducation.

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