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Week three notes

by: Brittany Lopez

Week three notes Psy 7 RMH

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Brittany Lopez

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Qualitative Analysis & Thematic Analysis
Research Methods for Mental Health
Dr Zoë Boden
Class Notes
research, research methods, Psychology
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This 7 page Class Notes was uploaded by Brittany Lopez on Monday October 17, 2016. The Class Notes belongs to Psy 7 RMH at LSBU taught by Dr Zoë Boden in Fall 2016. Since its upload, it has received 2 views. For similar materials see Research Methods for Mental Health in Psychology at LSBU.

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Date Created: 10/17/16
Qualitative Analysis & Thematic Analysis Week 3  Transcripts o The stage between data collection and data analysis o Turning audio (or visual) recordings into a text form  Better developed for auditory than visual recordings  Loss of some info from original source in the transcription process  Different levels of transcriptions  Features of talk o Some transcription techniques are better than others at coping with different  levels of feature  Prosodic features  How a word is spoken (softly, loudly, emphasis)  Paralinguistic features  E.g. words spoken with a laugh or a sigh  Extralinguistic features  E.g. gestures and facial expressions  Transcript o Verbatim=word for word, interviewer and participant o Basic transcription for qualitative research should include  Stutters, 'erms' and 'ums'  Non­verbal info  Significant pauses  Emphasis  Places where you can't tell what is being said o Include a key to show which notation used  The Jefferson System o One method of transcribing language data­ very detailed (See also Jefferson­lite) o Provides conventions for transcribing using a normal QWERTY keyboard  Records info such as errors of speech, emphasis, pauses, nonverbal aspects and people talking over one another or speaking at the same time, and turn  taking errors o Represents the material as a social exchange  The perils of transcription o Decisions about how data are collected will affect what info is retained and what  is lost  Subtle nuances may be lost o Make sure you select the method best suited to the analysis that you want to carry  out  Jefferson system is very detailed and thus very time­consuming  Not worthwhile if you're only interested in the content, not how the words are spoken and/or gestures o Errors frequently occur in transcriptions  Verbal additions, deletions, relocations and substitutions often occur o Always check the completed transcription against the original source o And/or a colleague to check the veracity of your transcriptions  Data Analysis o Qualitative analysis is an involved and intensive process o There is often no clear separation between data collection and analysis  Ongoing reflexive process involving adapting the data collection  Reflecting both the emerging data (what the participants have said) and  adapting to best answer the research question  Research diaries o Most analysis involves some combination of  Organizing and categorizing the data  Linking what has been found to broader social processes or theoretical  concepts  Some types of Analyses o Grounded theory  o Discourse analyses  Foucauldian discourse analysis  Discursive psychology o Dialogical analysis o Framework analysis o Template analysis o Conversation analysis o Narrative analyses o Thematic analysis o Psychoanalytic approaches o Descriptive phenomenology o Hermeneutic phenomenologies Lifeworld's phenomenology   Interpretative phenomenological analysis  Q­Methodology  Doing data analysis o Some common stages/processes  Immersion  Intensive reading and/or listening to material  Categorization  Assigning codes or categories, or identifying meanings  systematically  Reduction/distillation  Refining and distilling the categories/meanings. Going to a more  conceptual or abstract level Broader interpretation   Making sense of the data from a wider perspective. Making link  between theory and data  Thematic Analysis o A method for identifying, analyzing and reporting themes or patterns in data o Minimizing, organizes and describes your data set o But describe it in rich detail o It (usually) also allows for interpretation of the data o There are a range of different types of TA  Perspectives on TA o Traumatizing meanings one of few shared generic skills across qualitative  analysis (Holloway and Todres, 2003) o TA is a 'foundational method' o Thematic analysis is an analytic method in its own right (Braun and Clarke, 2006) o …others see it as a 'quick and dirty' method (Dallos and Vetere, 2005, p. 62)  What is a theme? o  how do we know what counts as a theme? o A theme is a significant strand/idea/concept within the data o It can be something that reoccurs frequently­­ a motif o It can have special importance theoretically or seem particularly important for  participant  TA Approaches o Ontology/epistemology  It can be more realist/essentialist or more relativist/constructionist o Approach  Inductive or theory­led  An inductive approach sets­aside assumptions/beliefs/experiences and the  theories available. 'bottom­up', grounding all ideas in the data  Theory­led works from specific theoretical frame, using this to influence  the development of themes o Levels of analysis  Descriptive (Semantic, surface­level)  Latent (interpretative, critical, questioning) Step 1: Familiarize yourself with data  o Transcribing data (if necessary) o Reading and re­reading the data o Noting down initial ideas  Step 2: initial coding o Data is coded line by line looking to identifying what is in the data o This is the first step in organizing the data o Codes need to be written next to the appropriate bit of text o You're attempting to paraphrase the content of the text o You may also start to use more psychological language o Codes tend to be quite specific, you may have quite a lot of them, even for a short  piece of text  Step 3: Searching for Themes o Look for connections between the codes­these are your themes o Themes are broader and less specific than codes o You are aiming for as few themes as possible (2­5) o But you are trying to cluster all codes into themes o You can develop this process visually (mind­maps) or by creating lists of things  that seem to go together (excel, word, by hand) o Sometimes a code doesn’t seem to fit anywhere­it's a good idea to create a  miscellaneous theme­ those codes may well fit later on, or a small number be  discarded  Step 4: Review of Themes o Examine your themes against the original data­ does the theme have enough data  to support it? o Draw all the evidence (extracts from the transcripts) relating to the same theme  and paste it into one document o Give page and line numbers for each extract o A theme may need to be split or subdivided­each theme may have 2­3 sub­themes o A theme should aim to fully fit the data (although in large data­sets this is  difficult)  Step 5: Theme Definition and Labelling o Can your theme be successfully differentiated from other themes? o Choose a title/label that is punchy and concise. It should immediately help reader  understand what theme is about o Can you say exactly what theme is about and what it's not about… in just couple  of sentences? o Best share you ideas about what a theme is with other to check for validity What not to do  o You should not use your interview questions to create themes o A weak analysis may be indicated by themes which overlap too much or where  there is a lack of consistency or coherence o Make sure your themes capture what is in the data, not your assumptions about  the topic  Evidencing your themes o It's typical to include verbatim quotes from the participant/s o A pseudonym or number is used to avoid identifying the participant (for ethical  reasons) o Numbers are sometimes seen to be de­humanizing, so many researcher prefer to  pick appropriate pseudonyms for their participants o Quotes shouldn't be too long, or too short o Your analysis should be longer than the quote o But quote needs enough context that it provides good evidence and allows the  reader to understand what is happening   How to DO analysis o Two approaches  With a computer  Specialist programs  Excel, word  By hand  Post­its  Diagrams  Lists  Or a mixture of the two  Computer analysis o One tool that can help with analysis  CAQDAS (computer­assisted qualitative data analysis software) o Cuts down on amount of paper  Much textual material to keep under control  Line­numbered transcripts, coding categories, evolution of these  categories o Useful for making and changing links within (and between) documents o Quick recording of data, allowing for changes to categories and additional data  Writing up Qualitative Research o Title o Intro o Methods  E.g. participants and recruitment, ethics, reflexivity data collection, data  analysis o Findings o Discussion o References o Appendices  Writing up Qualitative Research: Intro o Similar to quantitative reports  Aims  Why does this matter? o Literature review  What do we know about this area already? o Rational for this study  Sometimes justifies the use of a qualitative methodology or introduces the  approach a little o Research question(s)­ NO hypothesis!  Writing up Qualitative Research: Method o Sections typically include  Participants (and recruitment)  Ethical considerations  Data collection­how you collected your data, which approach and why,  details of the procedure involved  Data analysis­ how you did your analysis, which method you used and  why details of the procedures involved (steps)  Writing up Qualitative Research: Findings o For a thematic analysis  Intro to the themes  Sub­sections with each of the theme titles as the headings  In each theme section, a short intro to the theme including any  subthemes  Analysis written up as a narrative commentary under each theme  A selection of quotations to illustrate your analytic comments  (with pseudonyms, page and line numbers as appropriate)  A brief concluding paragraph or short summary  This can review the themes and point out any links between them  Writing as Analysis o Writing up is the final step o Connections are made o Contradictions are spotted o Themes are refined and may be integrated or collapsed further  Tips for writing up the analysis o Ensure you have sufficient extracts from the data to support your themes o Provide clear descriptions of each theme when you introduce it o Make your thematic analysis go beyond simple description and show how the  themes address the research question o Choose rich data examples to illustrate each theme o Don't over­sample extracts from one participant­ make sure everyone's voice is  heard Include a table or diagram of your cross­case analysis o  Evidencing your themes o It's typical to include verbatim quotes from the participant/s o A pseudonym or numbers is used to avoid identifying the participant (for ethical  reasons) o Numbers are sometimes seen to be de­humanizing, so many researcher prefer to  pick appropriate pseudonyms for their participants (or have them pick) o Quotes shouldn't be too long or too short o Your analysis should be longer than the quote, but quote needs enough context  that it provides good evidence and allows reader to understand what is happening  When to use literature to support your claims o Two ways of doing this  Save all discussion of literature for discussion section  Integrate literature with the findings and then have a General Discussion at the end Writing up Qualitative Research: Discussion   Much like an APA quantitative report o Start with a summary of the findings o Make links with previous literature, including empirical and theoretical work o Can introduce new studies here­as your research is exploratory it may have gone  in new and unexpected directions. The discussion is the time to explore these in more  depth o Reflexive statement­how has the researcher shaped the data? o Clinical and research implications Limitations/evaluation o o conclusion


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