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# Analisa Tematik (Thematic analytic)

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Analisa Data pada Penelitian Kualitatif: Pendekatan Analisa Tematik

Analisa Data pada Penelitian Kualitatif: Pendekatan Analisa Tematik

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### Analisa Tematik (Thematic analytic)

1. 1. Introduction ofThematic Analysis Najmah, SKM, MPH, PhD Fb: Najmah Usman/ Ig Najmahusman.7/ E: najmah@fkm.unsri.ac.id
2. 2. MyQuote Ketika epidemiologist dan statistician perlu belajar mengolah KATA, selain ANGKA Kesehatan masyarakat itu kompleks kedua ilmu olah KATA dan ANGKA akan saling melengkapi untuk memahami fenomena yang ada (Najmah)
3. 3. Research Onion (Sauders) Analysis of Saunders Research Onion: https://thesismind.com/analysis-of-saunders-research-onion/
4. 4. "Rubbish in- RubbishOut" "Garbage in- GarbageOut"
5. 5. TODAY’s TOPICS What is thematic Analysis Steps inThematic Analysis Example and Exercises
6. 6. Thematic Analysis A method for identifying, analysing and reporting patterns (themes) within data. It minimally organises and describes your data in (rich) detail However, frequently it goes further than this, and interprets various aspects of the research topics  (Braun & Clarke, 2006: 79) Clarke, V., Braun, V., & Hayfield, N. (2015). Thematic analysis. Qualitative psychology: A practical guide to research methods, 222-248.
7. 7. Coding reliability Thematic Analysis Deductive (theory-driven) approach more common  Familiarisation  Theme development  Coding (development of coding frame)  Test Reliability of coding frame Braun Calrke & Hayfield, 2019,Thematic Analysis Part 1:https://www.youtube.com/watch?v=Lor1A0kRIKU
8. 8. Reflective Thematic Analysis Inductive (data-driven) approach more common  Familiarisation  Coding (organic and subjective; one coder)  Theme development (review initial themes agains coded data and entire data-set; subjectice and interpretive) Braun Calrke & Hayfield, 2019,Thematic Analysis Part 1:https://www.youtube.com/watch?v=Lor1A0kRIKU
9. 9. Themes  Themes as ’domain summaries  Fully-realised (shared meaning)  shared meading underpinned by a central concept   multi-faceted; tell a story about the data  Themes-Analytic input? Output?   developed early on and guide coding   developed later and represent the outcome of coding  Themes-buried treasure or built by the researcher?   themes are understood as actively created by teh researcher   theme generation occurs at the intersection of the data and teh researcher’s interpretative framework, prior training, skill, assumption, etc Braun Calrke & Hayfield, 2019,Thematic Analysis Part 1:https://www.youtube.com/watch?v=Lor1A0kRIKU
10. 10. Steps in Thematic Analysis  Familiarisation with the data entailed reading the transcripts multiple times to immerse myself in the data  Coding and recoding were performed manually to find patterns, and to filter and analyse the data based on my own lens, and discover meaningful phrases and ideas  Categorising was performed as a process of dividing, grouping, reorganising, and linking codes to make meaning and enhance understandings of the data  GeneratingThemes
11. 11. First step Familiarisation with the data entailed reading the transcripts multiple times to immerse myself in the data
12. 12. SecondStep Coding and recoding were performed manually to find patterns, and to filter and analyse the data based on my own lens, and discover meaningful phrases and ideas
13. 13. Third step: categorising was performed as a process of dividing, grouping, reorganising, and linking codes to make meaning and enhance understandings of the data FGDs Group A dan B Interviews A, B, C, & D FGDs with Group C, D, E FGD/Interview E, F, G, H, & I Figure 1: Data generation cycle of the field research HIV-POSITIVE WOMEN HEALTH AND NGO WORKERS POLICY MAKERS
14. 14. The coding manual for qualitative researchers The data analysis procedures are a means to provide meaningful information to answer research questions, But also, that researchers should use their mind and heart or reflection to generate rich and meaningful evidence  (Saldana, 2016) Saldana, J. (2016). The coding manual for qualitative researchers (J. Seaman Ed.). Los Angeles, CA: SAGE.
15. 15. Example of Coding andThemes
16. 16. NGO Workers’s FGD
17. 17. Health worker’s voices
18. 18. Health workers’ voices
19. 19. HIV-positive women’s voices
20. 20. EXAMPLEOF THEMES Barriers to accessing PMTCT service Getting tested or not Breaches of confidentiality The culture of kepo Health workers’ intention to protect their peers Lack of professionalism HIV screening is only being implemented for one year Lack of coordination and distrust between host organisations Inadequate and limited HIV training for midwives Relying on the subjective judgement of health workers HIV positive: Experiences after the diagnosis How the health system failed Ani Health workers’ fears of working with HIV positive women “It is normal” to be fearful of HIV infection Avoidance along a continuum The referral system: Endless red tape
21. 21. EXAMPLEOF THEMES Barriers to accessing PMTCT service Gendered morality: Discrimination and women’s access to PMTCT services Stories of Anti and Lela: Needing a husband permission to HIV testing HIV testing and the difficulty of implementation Unequal rights affecting women’s decisions around their own reproductive and sexual health Silenced voices of health professionals powerless to exercise their professional role Adel’s story: A woman is responsible for spreading HIV Lilis’ story: A woman’s space with a trained midwife in antenatal care services in puskesmas
22. 22. Bunga’s voices and lived experience List kode-kode yang muncul dalam transkript wawancara Bunga Kelompokkan kode-kode ini sesuai tema besar Buatlah mind mapping
23. 23. EXERCISE
24. 24. Mindmup.com
25. 25.  HAPPY PRACTICE  HAVE FUN IN QUALITATIVEAPPROACH  HAPPY RAMADHAN