Qualitative Research Tutorial Notes PDF

Tutorial 1-5 Week 3 Qualitative research: Content & thematic analyses Theory development Useful when understanding subjective experience 6 steps in qualitative research 1. Recording data 2. Transcription (...

Tutorial 1-5 Week 3 Qualitative research: Content & thematic analyses Theory development Useful when understanding subjective experience 6 steps in qualitative research 1. Recording data 2. Transcription (if necessary) 3. Familiarisation (read over your data, gain a deep understanding) 4. Coding (creating categories) & analysis 5. Theory development (Grounded theory — i.e. generating theory from data) 6. Testing/validation (quantitative/qualitative/mixed)  Analyses Conceptual analysis: Content analysis: Thematic analysis: investigating meaning examination of concepts themes & patterns within (i.e. the content) within communication examining how people communication understand terms (producing E.g. using certain grounded theories) language E.g what is happiness? Qualitative coding Codes: labels used to describe meaningful segments/relations 1st phase — Open coding: selecting & naming categories from the analysis of the data ‘Affect’ as category; anxiety & depression as sub-categories 2nd phase – Axial coding: Identifying relationships between sub-categories & categories Sub-varieties of a larger umbrella phenomenon? How do behaviour, cognition, social situations interrelate? What themes & patterns are there?  Grounded theory = generating theory from data build a theory using the categories & influences on the development of bulimia  Week 4 Critical Evaluation & Reproducibility in Psychology Is the theory behind the research presented adequately & in sufficient detail? Are the hypotheses presented clearly? Is the study designed to allow the hypotheses to be tested? Is the dependent variable operationalised appropriately Are the statistics appropriate? Include Correlation coefficient & the strength to allow readers to easily determine correlation Mention any outliers Report p-values  Week 5 Steps for secondary data analysis 1. Determine RQ (possibly tentative hypotheses) 2. Find appropriate dataset for your area / RQ 3. Identify the study’s design, variables 4. Refine hypotheses in light of actual variables 5. Analyse data 6. Make conclusions and write up results  Wide Format Useful for descriptive analysis & regression (i.e. predict wellbeing at time point 5)  Long Format Useful to analyze whether there is any change over time. A new variable called “wave” is included. Can conduct repeated measures ANOVA