DATA ANALYSIS QUALITATIVE - PowerPoint Presentation

1. DATA ANALYSISQUALITATIVEDR AKPOR

2. DATA ANALYSISThe purpose of data analysis is to organised, provide structure to and elicit meaning from the research dataQualitative analysis is very tasking and requires insight, ingenuity, creativity, conceptual sensitivity and sheer hard work (Polit & Hungler, 2001)As recognised by Parahoo (2006), data analysis in qualitative research start when the data is being collected and there after the researcher make judgement based on the data that is gotten relating it to the phenomenon that is under study.

3. DATA ANALYSIS CONTDJacelon and O’Dell (2005) said researcher serves as the instrument of data analysis because he explore and reflect on what have been discussed during the interview processAfter gathering life world descriptions of personal experience, each account become a ‘text’ that is ready for the analysis of meaning and for the formulation of these meaning into a coherent story of inter-related themes and insight

4. DATA ANALYSIS CONTDAnalysis of qualitative data (interview) involves transcribing of data verbatim and the researcher should make sure that it is accurately transcribed.Another step is organising data into classes and indexing them and data gotten is converted into smaller, more manageable unit that can be retrieved and review. The next step is encoding of schemes i.e placed into themes and categories (Polit & Beck, 2010).

5. 5ANALYSING QUALITATIVE DATAInterpretingReadingReducingDisplayingCodingOn fieldPost field5

6. CONTENT ANALYSISContent analysis is an approach used to quantify content in terms of predetermined categories and in a systematic and replicable manner (Bryman, 2012). Content analysis is an important strategy based on listing, counting and categorising participants’ words into text In content analysis, the most frequent word spoken or used by the participants is written down and the number of occurrence is noted and put in relevant text

7. CONTENT ANALYSIS CONTDListing is also important in content analysis because it shows not only the frequency of the word but also the position of the frequent words and it is used for data expansion rather than reducing And it involves replication of data in order to focus on the relevant word

8. STEPS IN QUALITATIVE DATA ANALYSISReading: Developing intimacy with dataReading for contentAre you obtaining the kind of data you expectedAre responses full and detailed or they are superficialBegin to identify emerging themes & explanationsNoting qualityCheck quality of transcripts e.g. non verbal interactions etc.Identify patternsIdentify transcripts from different sources e.g., different kinds of participants

9. STEPS IN QUALITATIVE DATA ANALYSISCoding: Identify Emerging themesFinancial decision making, Borrowing moneyCreating words that act as flags Examples: Financial decision making <FINDECISION>; Treatment seeking <TRITSEEK>; Pregnancy signs <PREGSIGNS>Computer soft wares can be used for codingCDC EZ-Text, Ethnograph, QSR N6, NVIVO

10. STEPS IN QUALITATIVE DATA ANALYSISLabeling and Displaying the data Distinguishing of differences of a topicData summarization in backgroundData Reduction: Getting the big pictureProcess of distilling the information to make visible the most essential concepts and relationshipsData presentation: Text quotes, Classifications and Flow Charts

11. EXAMPLE- QUALITATIVE DATA ANALYSIS The planning for the data analysis was as follows:Transcription of the audiotapes. Audiotapes were transcribed and the field notes were used to enhance and substantiate data in order to get an adequate transcriptionTesch’s data analysis approach. A data analysis protocol was develop based on Tesch‘s data analysis approach (Addendum E) (Creswell, 2003). Concurrent gathering and analysis of the data. In order to know when data saturation occurred, data analysis commenced with the first interview and continued as data was gathered.

12. EXAMPLE- QUALITATIVE DATA ANALYSIS CONTDIndependent coder. An independent coder, an experienced qualitative researcher, co-coded the transcribed data using the same approach to reduce bias in the data analysis. A consensus meeting was planned and held with the independent coder

13. EXAMPLE- QUALITATIVE DATA ANALYSIS DATA ANALYSIS PROTOCOLTesch’s approach to data analysis (Creswell, 2003), which provides a useful process to transcribing unstructured data in eight steps will be adopted for data analysis. The eight steps engage a researcher in a systematic process of analysing textual data. The steps are as follows: 1. Get a sense of the whole. Read all of the transcriptions carefully. Jot down some ideas as they come to mind.

14. EXAMPLE- QUALITATIVE DATA ANALYSIS 2. Take one document (one interview). Go through it and ask yourself what it is about? Do not think about the ‘respondent’ of the information, but rather the underlying meaning. Write thoughts in the margin.3. When you have completed this task for several informants, make a list of topics. Cluster together similar topics. Form these topics into columns that might be arrayed as major topics, unique topics and leftovers4. Now take the list and go back to your data. Abbreviate the topics as codes next to the appropriate segments of the texts. Try out this preliminary organizing scheme to see whether new categories and codes emerge.

15. EXAMPLE- QUALITATIVE DATA ANALYSIS 5. Find the most descriptive wording for your topics and turn into categories by grouping topics that relate to each other. Perhaps draw lines between your categories to show interrelationships.6. Make a final decision on the abbreviation for each category and alphabetize these codes.7. Assemble the date material belonging to each category in one place and perform a preliminary analysis.8. If necessary, recode your existing data.

16. DEMOGRAPHIC PROFILES OF PARTICIPANTSSection A: Demographic profileA1Socio-cultural group Sotho, Tswana, Pedi, Venda, Afrikaans, Ndebele, Xhosa, Tsonga, Swazi, Zulu and English A2AgeFive age groups between 13 and 50 yearsA3GenderMale or femaleA4Position in the communityTeenagers, parents, teachers, professional nurses and community leaders.TABLE 3.8: Demographic profile and pregnancy prevention programmes

17. SECTION BData gathering instrument An interview schedule (Addendum A) was developed based on the Community Assessment Wheel of the Community-as-Partner Model (Figure 1.2). The content and application of the interview schedule is shown in Table 3.6. 

18. EXAMPLE OF AN INTERVIEW SCHEDULECommunity assessment wheelInterview themesCommunity coreHistoryHistory regarding the high rate of teenage pregnancies in Soshanguve schools and its environsEthnicitySocio-cultural groups Demographic profilesAge, gender and position in the communityValues and beliefsMeaning, acceptance and cultural beliefs about datingCultural beliefs about teenage pregnancyRole in the prevention of teenage pregnancyCommunity subsystemsHealth and social servicesKnowledge and acceptance of contraceptives useSafetySchool safetyCommunicationSexuality education and communication and parentalparticipation in their child’s education

19. TRUSTWORTHINESSThe establishing of trustworthiness was according to the strategies promoted by Lincoln and Guba (1985: Chapter 11). Trustworthiness is a method of establishing rigour in qualitative research, without sacrificing relevance. Table 3.7 presents the strategies used to ensure the trustworthiness of the data. 

20. SATURATION AND ACHIEVEMENT OF REFERENTIAL ADEQUACY Saturation of data determined the sample size due to the qualitative nature of the sample. Table 4.1 provides the evidence of data saturation and referential adequacy.

21. DATA SATURATION AND ACHIEVEMENT OF REFERENTIAL ADEQUACYStakeholders interviewedNumber of interviewsNumber analysed with new categoriesNumber analysed without new categoriesTeachers15123Professional nurses15132Teenagers15123Parents15114Community leaders15123

22. EXAMPLE- QUALITATIVE DATA ANALYSIS Referential adequacy was attained, partially fulfilling the requirement of trustworthiness (Lincoln & Guba, 1985). Meaning of dating- The majority (10 of 15) of the teenagers explained that dating is going out to have fun or the connection between two people but does not include a sexual relationship. The following are some of the responses from the participants:“…is probably a connection between two people that are fond of each other and sometimes it develop into love or lust attraction and all that, no sex involved.”“Basically, it is going out with someone just to have fun but not getting too serious like having sex. No intimacy, it’s just having fun.”“Is an affection between two people, sharing the passion of love and feelings but it doesn’t include sex.”

23. EXAMPLE- QUALITATIVE DATA ANALYSIS Cultural beliefs about dating-When asked about cultural beliefs regarding dating, more than two thirds (13 of 15) of the teenagers indicated dating is not part of their culture. Some of their responses are:“Basically in my culture, dating is seen as a sin. It is unethical because the girl needs to wait until marriage.”“My culture does not accept dating yeah, it is seen as an abomination because it is seen as a way for teenagers to have sex.”“They think dating is wrong. I think they have this perception that your parents should choose a partner for you and you get married without dating. A woman should only see a man when she is ready to start a family.” 

24. EXAMPLE-DISCUSSION OF THE FINDINGS OF THE STUDYThe findings are discussed in terms of the findings of the main themes. 5.2.1 Community core: Values and beliefs 5.2.1.1 Meaning, acceptance and cultural beliefs about datingThe consensus with regard to the meaning of dating was a way of having fun but not sexual intimacy. Dating was acceptable for teenagers above 18 years, but it was not seen as culturally accepted behaviour. This study produced evidence to support this:The majority (59) of the participants defined dating as having fun, but it is not expected to include sexual relationship (Section 4.9.1.2).Fifty-nine (59) participants viewed dating as accepted behaviour by teenagers, parents and families (Section 4.9.1.2).

25. EXAMPLE-DISCUSSION OF THE FINDINGS OF THE STUDYAccording to the developmental stages of Erik Erikson by Arlene and Harder (2012), teenagers seem to seek one or more companions as well as love. As teenagers attempt to discover mutually satisfying relationships, through friendship and marriage, the successful ability to negotiate this stage can result in experiencing a deep level of intimacy. Isolation and distance from others can happen if this stage was unsuccessful (Arlene & Harder, 2012). Witmer (2013) indicated that it is normal for teenagers to be interested in dating, as it is a normal experience in adolescent life.

26. EXAMPLE-DISCUSSION OF THE FINDINGS OF THE STUDYAccording to Date Safe Project (2010) and Grundy (2010), the age of 16 years and above has been indicated as the right age for dating, provided the teenager is mature. In deciding the right age to begin dating, proper preparation is the key to helping teenagers make the safest choices. Such maturity should be measured by the willingness to sufficiently participate in household chores, treat others with respect, obtain good grades at school and manage emotions appropriately (Grundy, 2010).  

27. EXAMPLE-DISCUSSION OF THE FINDINGS OF THE STUDYAs found in the study, the majority of the participants (64 of 75) signified that most families do support their pregnant teenagers. Only a few (12 of 75), especially the professional nurses, believed teenage pregnancy had become an acceptable incident in the community. Two (2 of 15) teenagers and teachers, one (1 of 15) parent and community leaders and more than one third (6 of 15) of the professional nurses believed teenage pregnancy had become an acceptable incident in the community.