Analysing and presenting qualitative data

Chadwick5analysing and presenting qualitative data is one of the most confusing aspects of qualitative paper provides a pragmatic approach using a form of thematic content analysis. Approaches to presenting qualitative data are also process of qualitative data analysis is labour intensive and time consuming. Those who are unsure about this approach should seek appropriate ctthis paper provides a pragmatic approach to analysing qualitative data, using actual data from a qualitative dental public health study for demonstration purposes. The paper also critically explores how computers can be used to facilitate this process, the debate about the verification (validation) of qualitative analyses and how to write up and present qualitative research uctionprevious papers in this series have introduced readers to qualitative research and identified approaches to collecting qualitative data. However, for those new to this approach, one of the most bewildering aspects of qualitative research is, perhaps, how to analyse and present the data once it has been collected. This final paper therefore considers a method of analysing and presenting textual data gathered during qualitative ches to analysing qualitative datathere are two fundamental approaches to analysing qualitative data (although each can be handled in a variety of different ways): the deductive approach and the inductive approach. Essentially, the researcher imposes their own structure or theories on the data and then uses these to analyse the interview transcripts. The data analysis would then consist of examining each interview to determine how many patients had complaints of each type and the extent to which complaints of each type co-occur. However, while this approach is relatively quick and easy, it is inflexible and can potentially bias the whole analysis process as the coding framework has been decided in advance, which can severely limit theme and theory sely, the inductive approach involves analysing data with little or no predetermined theory, structure or framework and uses the actual data itself to derive the structure of analysis.

Inductive analysis is the most common approach used to analyse qualitative data2 and is, therefore, the focus of this a variety of inductive approaches to analysing qualitative data are available, the method of analysis described in this paper is that of thematic content analysis, and is, perhaps, the most common method of data analysis used in qualitative work. 5 this method arose out of the approach known as grounded theory,6 although the method can be used in a range of other types of qualitative work, including ethnography and phenomenology (see the first paper in this series7 for definitions). Indeed, the process of thematic content analysis is often very similar in all types of qualitative research, in that the process involves analysing transcripts, identifying themes within those data and gathering together examples of those themes from the example of an initial coding frameworkfull the second stage, the researcher collects together all of the words and phrases from all of the interviews onto a clean set of pages. The next stage is to allocate each of the categories its own coloured marking pen and then each transcript is worked through and data that fit under a particular category are marked with the according colour. Finally, all of the sections of data, under each of the categories (and thus assigned a particular colour) are cut out and pasted onto the a4 sheets. It is from this folder that the report of the findings can be discussed earlier, computer programmes can be used to manage this process and may be particularly useful in qualitative studies with larger datasets. However, this process is arguably more subjective than the process normally associated with quantitative data analysis, since a common belief amongst social scientists is that a definitive, objective view of social reality does not exist. For example, some quantitative researchers claim that qualitative accounts cannot be held straightforwardly to represent the social world, thus different researchers may interpret the same data somewhat differently. Consequently, this leads to the issue of the verifiability of qualitative data is, therefore, a debate as to whether qualitative researchers should have their analyses verified or validated by a third party.

There are two key ways of having data analyses validated by others: respondent validation (or member check) – returning to the study participants and asking them to validate analyses – and peer review (or peer debrief, also referred to as inter-rater reliability) – whereby another qualitative researcher analyses the data independently. 14, 15participant validation involves returning to respondents and asking them to carefully read through their interview transcripts and/or data analysis for them to validate, or refute, the researcher's interpretation of the data. Whilst this can arguably help to refine theme and theory development, the process is hugely time consuming and, if it does not occur relatively soon after data collection and analysis, participants may have also changed their perceptions and views because of temporal effects and potential changes in their situation, health, and perhaps even as a result of participation in the study. Respondents may also want to modify their opinions on re-presentation of the data if they now feel that, on reflection, their original comments are not 'socially desirable'. Furthermore, it is possible that some participants will not recognise some of the emerging theories, as each of them will probably have contributed only a portion of the data. Process of peer review involves at least one other suitably experienced researcher independently reviewing and exploring interview transcripts, data analysis and emerging themes. 16, 17 however, many researchers also feel that the value of this approach is questionable, since it is possible that each researcher may interpret the data, or parts of it, differently. Also, if both perspectives are grounded in and supported by the data, is one interpretation necessarily stronger or more valid than the other? Despite perpetual debate, there is no definitive answer to the issue of validity in qualitative analysis.

However, to ensure that the analysis process is systematic and rigorous, the whole corpus of collected data must be thoroughly analysed. This essentially involves reading and re-reading data to search for and identify emerging themes in the constant search for understanding and the meaning of the data. 19 where appropriate, researchers should also provide a detailed explication in published reports of how data was collected and analysed, as this helps the reader to critically assess the value of the should also be noted that qualitative data cannot be usefully quantified given the nature, composition and size of the sample group, and ultimately the epistemological aim of the g and presenting qualitative researchthere are two main approaches to writing up the findings of qualitative research. Below are brief examples of the two approaches, using actual data from a qualitative dental public health study that explored primary school children's understanding of food. As in quantitative research, these supporting chapters would also be used to develop theories or hypothesise about the data and, if appropriate, to make realistic conclusions and recommendations for practice and further e b (combined findings and discussion chapter):copying friendsin this study, as with others (eg ludvigsen & sharma21 and watt & sheiham22), peer influence is a strong factor, with children copying each other's food choices at school meal times:girl: 'they say "copy me and what i have. Further guidance on writing up qualitative reports can be found in the sionthis paper has described a pragmatic process of thematic content analysis as a method of analysing qualitative data generated by interviews or focus groups. The paper also briefly illustrates two different ways of presenting qualitative reports, having analysed the analysis process, when done properly, is systematic and rigorous and therefore labour-intensive and time consuming. Consequently, for those undertaking this process for the first time, we recommend seeking advice from experienced qualitative of pagereferencesspencer l, ritchie j, o'connor w. Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?

Validity in qualitative health care research: an exploration of the impact of individual researcher perspectives within collaborative enquiry. Gill2 e-mail: pwgill@l homeadvance online you startpreparationsubmissionpost sions and jobsbdj marketplaceinformation collectionsbdj cpdbdj top ten h dental ibe to british dental ibe to british dental e navigation - this issuetable of contents for this issueprevious articlenext ad pdfsend to a ef lists 177 articles citing this articlescopus lists 202 articles citing this articleexport citationexport referencesrights and e navigationabstractintroductionapproaches to analysing qualitative datadata collection and data analysiswriting and presenting qualitative researchconclusionfigures, schemes & tablesbox 1referencessearch pubmed forp. Rnablast (basic local alignment search tool)blast (stand-alone)e-utilitiesgenbankgenbank: bankitgenbank: sequingenbank: tbl2asngenome workbenchinfluenza virusnucleotide databasepopsetprimer-blastprosplignreference sequence (refseq)refseqgenesequence read archive (sra)spligntrace archiveunigeneall dna & rna resources... Softwareblast (basic local alignment search tool)blast (stand-alone)cn3dconserved domain search service (cd search)e-utilitiesgenbank: bankitgenbank: sequingenbank: tbl2asngenome protmapgenome workbenchprimer-blastprosplignpubchem structure searchsnp submission toolsplignvector alignment search tool (vast)all data & software resources... Structuresbiosystemscn3dconserved domain database (cdd)conserved domain search service (cd search)structure (molecular modeling database)vector alignment search tool (vast)all domains & structures resources... Expressionbiosystemsdatabase of genotypes and phenotypes (dbgap)e-utilitiesgenegene expression omnibus (geo) database gene expression omnibus (geo) datasetsgene expression omnibus (geo) profilesgenome workbenchhomologenemap vieweronline mendelian inheritance in man (omim)refseqgeneunigeneall genes & expression resources... Medicinebookshelfdatabase of genotypes and phenotypes (dbgap)genetic testing registryinfluenza virusmap vieweronline mendelian inheritance in man (omim)pubmedpubmed central (pmc)pubmed clinical queriesrefseqgeneall genetics & medicine resources... Mapsdatabase of genomic structural variation (dbvar)genbank: tbl2asngenomegenome projectgenome protmapgenome workbenchinfluenza virusmap viewernucleotide databasepopsetprosplignsequence read archive (sra)spligntrace archiveall genomes & maps resources... Basic local alignment search tool)blast (stand-alone)blast link (blink)conserved domain database (cdd)conserved domain search service (cd search)genome protmaphomologeneprotein clustersall homology resources...

Utilitiesjournals in ncbi databasesmesh databasencbi handbookncbi help manualncbi news & blogpubmedpubmed central (pmc)pubmed clinical queriespubmed healthall literature resources... Basic local alignment search tool)blast (stand-alone)blast link (blink)conserved domain database (cdd)conserved domain search service (cd search)e-utilitiesprosplignprotein clustersprotein databasereference sequence (refseq)all proteins resources... Of genomic structural variation (dbvar)database of genotypes and phenotypes (dbgap)database of single nucleotide polymorphisms (dbsnp)snp submission toolall variation resources... Toall how tochemicals & bioassaysdna & rnadata & softwaredomains & structuresgenes & expressiongenetics & medicinegenomes & mapshomologyliteratureproteinssequence analysistaxonomytraining & tutorialsvariationabout ncbi accesskeysmy ncbisign in to ncbisign : abstractformatsummarysummary (text)abstractabstract (text)medlinexmlpmid listapplysend tochoose destinationfileclipboardcollectionse-mailordermy bibliographycitation managerformatsummary (text)abstract (text)medlinexmlpmid listcsvcreate file1 selected item: 18438371formatsummarysummary (text)abstractabstract (text)medlinexmlpmid listmesh and other datae-mailsubjectadditional texte-maildidn't get the message? Ing and presenting qualitative d p1, gill p, stewart k, treasure e, chadwick information1cardiff school of nursing and midwifery studies, ty dewi sant, heath park, cardiff, cf14 ctthis paper provides a pragmatic approach to analysing qualitative data, using actual data from a qualitative dental public health study for demonstration purposes. The paper also critically explores how computers can be used to facilitate this process, the debate about the verification (validation) of qualitative analyses and how to write up and present qualitative research : 18438371 doi: 10. 292 [indexed for medline] sharepublication type, mesh termspublication typevalidation studiesmesh termsabstracting and indexing as topicdata collectiondental research*humansinterviews as topicqualitative research*writinglinkout - more resourcesfull text sourcesnature publishing grouppubmed commons home. The paper also critically explores how computers can be used to facilitate this process, the debate about the verification (validation) of qualitative analyses and how to write up and present qualitative research of sor of nursing, cardiff school of nursing and midwifery studies, ty dewi sant, heath park, cardiff, cf14 research fellow, faculty of health, sport and science, university of glamorgan, pontypridd, cf37 ch fellow, academic unit of primary care, university of bristol, bristol, bs8 , school of dentistry/professor of dental public health, cardiff university, heath park, cardiff, cf14 sor of paediatric dentistry, dental health and biological sciences, school of dentistry, cardiff university, heath park, cardiff, cf14 pondence to: p. Related slideshares at ative data n nigatu haregu, phd hed on mar 6, presentation summarizes qualitative data analysis methods in a brief manner.

Read and use for your qualitative you sure you want message goes you sure you want message goes er, university of technology and education, ho chi minh city, viet sity of presentation is definitely helpful for my knowledge of conducting a qualitative research project. I hope it can be you sure you want message goes consumer products ion specialist _unicef nutrition specialist _ ative data e of the presentationqualitative researchqualitative dataqualitative analysisqualitative softwarequalitative reporting ative research is qualitative research? Pope & mays bmj 1995;311:42-45 ions of qualitative methodsunderstanding context• how economic, political, social, cultural, environmental and organizational factors influence healthunderstanding people• how people make sense of their experiences of health and diseaseunderstanding interaction• how the various actors involved in different public health activities interact each other vs quan: basic differences qualitative quantitativepurpose to describe a situation, to measure magnitude-how gain insight to particular widespread is a practice... No pre-determined pre-determined response response categories categories, standard measuresdata in-depth explanatory data wide breadth of data from large from a small sample statistically representative sampleanalysis draws out patterns from tests hypotheses, uses data to concepts and insights support conclusionresult illustrative explanation & numerical aggregation in individual responses summaries, responses are clusteredsampling theoretical statistical vs quan: analytic approaches quantitative qualitativeresearch question fixed/focused broader, contextual, flexibleexpected outcome identified in usually not predefined, advance emergent research questionhierarchy of phases linearity circularconfounding factors controlled during searched in the field design & analysistime dimension slower rapid to slower vs quan: data collection method quantitative qualitativesampling random sampling open ended and less structured protocols (flexible)tools structured data depend on interactive collection instruments interviewsresults produce results that produce results that give generalize, compare and meaning, experience and views summarize for combining qual-quan methods qual-quan combining models sequential use model concurrent use modelqual-quan quan-qual quan qual quan qual model model model model ant concepts in designing qualitative researchconcept descriptionnatural setting participants are free from any control & data are collected in their natural environmentholism the whole is more than the sum, take magnitude of contextual factors in to accounthuman as a researcher is involved in every step being responsive,research flexible, adaptive and good listenerinstrumentemergent design study design emerges as further insights are gained through data collection and analysissaturation or a stage where additional interview or observation is notredundancy believed to add new information-enough is enough! Qualitative study designsstudy design descriptionethnography portrait of people- study of the story and culture of a group usually to develop cultural awareness & sensitivityphenomenology study of individual’s lived experiences of events-e. The experience of aids caregrounded theory going beyond adding to the existing body of knowledge-developing a new theory about a phenomenon-theory grounded on dataparticipatory action individuals & groups researching their own personalresearch beings, socio-cultural settings and experiencescase study in-depth investigation of a single or small number of units at a point (over a period) in time. Evaluation of s service ng in qualitative research • to generate a sample which allows understanding the social process aim of interest • purposive sampling- selection of the most productive sample to answer the research questiontechnique • ongoing interpretation of data will indicate who should be approached, including identification of missing voices • the one that adequately answers the research question-until new size categories, themes or explanations stop emerging from the data • depend on available time and resources ng techniques in qualitative research snow ball/chain  extreme/deviant  homogeneous  sampling case sampling sampling maximum  convenience  opportunistic variation sampling sampling sampling ative data of qualitative datastructured text, (writings, stories, survey comments,news articles, books etc)unstructured text (transcription, interviews, focusgroups, conversation)audio recordings, musicvideo recordings (graphics, art, pictures, visuals). Data collection methodsmethods brief explanationobservation the researcher gets close enough to study subjects to observe (with/without participation) usually to understand whether people do what they say they do, and to access tacit knowledge of subjectsinterview this involves asking questions, listening to and recording answers from an individual or group on a structured, semi-structured or unstructured format in an in-depth mannerfocus group focused (guided by a set of questions) and interactivediscussion session with a group small enough for everyone to have chance to talk and large enough to provide diversity of opinionsother methods rapid assessment procedure (rap), free listing, pile sort, ranking, life history (biography) ons for qualitative interviewstypes of examplesquestionshypothetical if you get the chance to be an hiv scientist, do you think you can discover a vaccine for hiv? Of qualitative questions• experience: when you told your manager that the project has failed, what happened?

Ing transcripttranscribe word by word (verbatim)consider non-verbal expressionstry to do the transcribing yourselfbe patient-time consuming ing metadata(log)project/research titledate of data collectionplace of data collectionid-code of informant(s)research teammethod of data collectiondocumentation type: tape recorder, notesand observations ative analysis is qualitative data analysis? Data analysis (qda) is the range ofprocesses and procedures whereby we move from thequalitative data that have been collected into some formof explanation, understanding or interpretation of thepeople and situations we are is usually based on an interpretative idea is to examine the meaningful and symboliccontent of qualitative data http:///intro_qda/what_is_ ches in analysisdeductive approach – using your research questions to group the data and then look for similarities and differences – used when time and resources are limited – used when qualitative research is a smaller component of a larger quantitative studyinductive approach – used when qualitative research is a major design of the inquiry – using emergent framework to group the data and then look for relationships ative vs quantitative data analysisqualitative quantitative• begins with more general • key explanatory and open-ended questions, outcome variables moving toward greater identified in advance precision as more • contextual/confounding information emerges variables identified and• pre-defined variables are controlled not identified in advance • data collection and• preliminary analysis is an analysis distinctly inherent part of data separate phases collection • analysis use formal statistical procedures for helping the analytical processsummaries: should contain the key points thatemerge from undertaking the specific activityself memos: allow you to make a record of theideas which occur to you about any aspect ofyour research, as you think of themresearcher used in qualitative data analysistheory: a set of interrelated concepts, definitions and propositionsthat presents a systematic view of events or situations by specifyingrelations among variablesthemes: idea categories that emerge from grouping of lower-leveldata pointscharacteristic: a single item or event in a text, similar to anindividual response to a variable or indicator in a quantitativeresearch. It is the smallest unit of analysiscoding: the process of attaching labels to lines of text so that theresearcher can group and compare similar or related pieces ofinformationcoding sorts: compilation of similarly coded blocks of text fromdifferent sources in to a single file or reportindexing: process that generates a word list comprising all thesubstantive words and their location within the texts entered in to aprogram ples of qualitative data analysis1. Exceptional cases may yield insights in to a problem or new idea for further inquiry es of qualitative data analysis• analysis is circular and non-linear• iterative and progressive• close interaction with the data• data collection and analysis is simultaneous• level of analysis varies• uses inflection i. This was good”• can be sorted in many ways• qualitative data by itself has meaning, i. Apple” ng, collecting and thinking model think  collect  about  things things notice things process of qualitative data analysisstep 1: organize the datastep 2: identify frameworkstep 3: sort data in to frameworkstep 4: use the framework for descriptive analysisstep 5: second order analysis 2: identify a framework• read, read, read... Identify a framework – explanatory – guided by the research question – exploratory-guided by the data• framework will structure, label and define data• framework=coding plan 3: sort data in to framework• code the data• modify the framework• data entry if use computer packages http:///intro_qda/how_what_to_ 4: use framework in descriptive analysis• descriptive analysis – range of responses in categories – identify recurrent themesstop here if exploratory research 5: second order analysis• identify recurrent themes• notice patterns in the data• identify respondent clusters – search for causality – identify related themes• build sequence of events• search data to answer research questions• develop hypothesis and test of qualitative analysis• content analysis• narrative analysis• discourse analysis• framework analysis• grounded theory http:/// t analysis• content analysis is the procedure for the categorization of verbal or behavioural data for the purpose of classification, summarization and tabulation• the content can be analyzed on two levels – descriptive: what is the data? Control, recruitment, decision-making, socialization, communication)• issues: illuminating key issues – how did participants change y in qualitative studiescriteria issues solutioncredibility truth value prolonged & persistent observation,(=internal validity) triangulation, peer-debriefing, member checks, deviant case analysistransferability applicability thick description, referential adequacy,(=external validity) prevention of premature closure of the data, reflexive journaldependability consistency dependability audit(=reliability) reflexive journalconformability neutrality conformability audit(=objectivity) reflexive journal http:///intro_qda/qualitative_ ative software ng and using computer software• it is possible to conduct qualitative analysis without a computer• concerns: relying too much on computers shortcuts will impede the process by distancing the researcher from the text• advantages: ease the burden of cutting and pasting by hand, and produce more powerful analysis by creation and insertion of codes in to text files, indexing, construction of hyperlinks, and selective retrieval of text segments ative analysis with softwares• with qualitative softwares, your workflow will be similar, but each step will be made easier by the computer’s capability for data storage, automated searching and display. You can use text, picture, audio and video source files directly• you can assign codes manually (autocode) to any section of text, audio or video or part of a picture• analysis is easy with the report feature, where you can select a subset of cases and codes to work with, choose what data to use, and sort your reports automatically http:/// of computer software in qualitative studies1) transcribing data2) writing/editing the data3) storage of data4) coding data (keywords or tags)5) search and retrieval of data6) data linking of related text7) writing/editing memos about the data8) display of selected reduced data9) graphic mapping10) preparing reports http:///intro_caqdas/what_the_sw_can_ to choose software - key questionstype and amount of datatheoretical approach to analysistime to learn vs time to analyzelevel of analysis (simple or detailed)desired “closeness” to the dataany desired quantification of resultsindividual or working as a teampeer software support availableany cost constraints (weitzman and miles 1995; lewins and silver 2005).

G a qualitative report g qualitative reportqualitative research generates rich information- thus deciding where to focus and the level of sharing is very challenging. Focus – academic: conceptual framework/theories, methodology and interpretation – practitioners: concrete suggestions for better practice, policy recommendations – lay readers: problem solving, reform on practice/policy ions in the report format• problem-solving approach (problem-based)• narrative approach (chronological)• policy approach (evidence-based)• analytic approach (theory/conceptual framework based) ing qualitative research• typically use quotes from data – descriptive – direct link with data – credibility• ways to use quotes – illustrative – range of issues – opposing views ing without quotes• list range of issues• rank or sequence issues• describe types of behaviour, strategies, experiences• report proportions (most, many, the majority)• flow diagrams: decision-making, event sequencing etc retation• interpretation is the act of identifying and explaining the core meaning of the data• organizing and connecting emerging themes, sub-themes and contradictions to get the bigger picture-what it all means – think how best to integrate data from multiple sources and methods• make generalization-providing answers to questions of social and theoretical significance• ensuring credible or trustworthy interpretations rd report format1. References -based elearning course - linkedin cation of course - linkedin ng techniques: project-based course - linkedin tative data ative data analysis (steps). Data analysis r 10-data analysis & mae nalzaro,bsm,bsn, analysis analysis tation, analysis and interpretation of sent successfully.. References board essential course - linkedin oint: using photos and video effectively for great course - linkedin thinking course - linkedin tative data ative data analysis (steps).