As mentioned above, 7 open ended questions were added at the end of CEDV. Inclusion of these open-ended (inductively coded) questions in survey added the richness of the survey data and made it more like a feminist version of survey rather than just being the positivist and behaviourist approach of quantitative research and the worth of this approach will be evident in the following chapter of results.
Responses to open-ended questions were analyzed by using qualitative content analysis. Hsieh and Shannon (2005) defined qualitative content analysis as “a research method for the subjective interpretation of the content of text data through the systematic classification process of coding and identifying themes or patterns”. This analysis uses code categories emerging from the data and after taking careful readings of the data, these codes are applied to take counts which then are used for examining the patterns to guide further interpretations of the data (Morgan, 1993).
I adopted this approach for analysing my survey open-ended questions because: a) this method is considered more appropriate when the research calls for the benefits of content analysis in describing the data patterns as well as for the advantages of grounded theory in interpreting the possible meanings and reasons behind such data patterns (Morgan, 1993); and b) I feel that it is also more close to the standpoint of feminist researchers as it emphasizes the need to understand the meanings than words while coding the data and at the level of interpreting results, it seeks for a greater
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understanding of data patterns rather than merely relying on numeric summaries. Therefore, I have used both an inductive research approach and back support by existing theory following the approach of Kloss (2010) in doing qualitative content analysis.
To analyse the data, following steps were taken: a) initially, after going through 50 out of 1046 questionnaires randomly for careful and repeated reading of the responses to each question, the word/phrase that appeared to be significant/relevant answer to the question was highlighted/ underlined. Themes and meaning not directly communicated in words were also identified and a keyword or phrase that captured the latent meaning was written in the margin of the paper. A sample of how codes and themes were identified is as follows:
Question 1: could you please share with me about your emotional experience at the time when your father was hurting your mother mentally or/and physically?
Respondent X: I have seen my mother being psychologically tortured since always/ever. Inside, I got hurt that even such a good and loyal wife could not get respect. Her life was destroyed. Actually father does it because of work stress.
Now, if we look for the words to do our coding, apparently the coding category of this emotional experience emerges as ‘felt hurt’, but reading the meaning of words carefully reveals that a ‘feeling of pity for mother’ is also there. Moreover, carefully examining the last sentence of this response shows that a ‘feeling of confusion’ about whether to blaming/defending or not blaming/defending father is also there.
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After open coding of 50 questionnaires, preliminary codes were decided and I started entering the open-ended data using these codes in SPSS and kept adding new codes when the data did not fit into an existing code. Silverman (2000) also stressed the continuous review of data while coding for not missing out data that does not fit into the categories. The basic purpose of coding process was to organize the varied responses of participants into interpretable categories (pattern or themes that are directly expressed in the text or are derived from them). Hence, it is crucial to define the categories very carefully and to watch out for potentially important data outside the categories.
While data entry, four new i.e., contradiction, defending abuse, blaming mother for abuse, and domestic violence by in-laws were emerged which, though, had not a direct relationship to the questions asked but they are very relevant to the phenomenon of IPV and would help in determining future directions of research on IPV in Pakistan. This was done by using constant comparison method (Glaser & Straus, 1967) which requires constantly comparing coding categories with the previous incidents in the same and different groups coded in the same category.
One thing that I observed while reading the answers on all questions was that on first question in which the word ‘father mentally or physically hurt mother’ was used, many participants replied in ‘it never happened’, but in the next questions where they are simply asked about their reactions, coping strategies, impact of witnessing IPV on themselves in that situation’, they shared their responses very openly. This pattern of responding to the questions is very crucial and I have also observed it while feeding the close ended data of CEDV into SPSS i.e. on direct questions about abuse or where
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the word ‘mentally or physically hurt’ is used participants have a problem in disclosure. This issue is also highlighted by other researchers working on sensitive issues (Luyt, 2008). Therefore a new theme ‘contradiction’ was identified which explores the presence of contradictory statements while responding to all questions. The reason behind ‘defending abuse’ category was that it was evident in many responses that participant were using words or phrases which reflected their attitudes and beliefs towards IPV and conveying that abuser was right in doing so. A sample statement from a participant is as follows: “father’s purpose of behaving such way has always been to correct mother which is his duty”.
Similarly, some participants pointed out that father only behaved badly and treated mother inhumanly when provoked by his mother/sisters/brother, hence, the category of ‘domestic violence’ emerged. Moreover, some of the participants wrote like (a sample response) “it is mother’s fault because if dad gets angry on contacting her relatives, she should avoid this but she is irresponsible”. Initially I thought to merge this category with ‘defending abuse’ , but after reading some more responses like these, I felt it should emerge as a separate category as it is more than just defending abuser and it was also blaming mother.
Once, all questionnaires had been coded and fed into SPSS, I critically started reviewing these coding categories within a particular question and some codes were combined during this process. Furthermore, at some points I had to decide which categories better serve the purpose of the research as some insights seemed less relevant than others and a few categories, e.g. the ‘denial’, and ‘indifferent’ were left out completely. Finally, the process of counting codes was done by running descriptive analysis (frequency and percentages).
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As the main objective of asking these open-ended questions was to learn about emotional experiences, reaction, impact, coping strategies and protective factors for the young adults affected by IPV, therefore, nonresponse and neutral mentions e.g., never happened, not applicable, do not know, do not want to share etc. were ignored and only relevant information regarding the issue of IPV were analysed. In the final tabulations, low frequency codes were merged or taken as a subcategory into some more general category which was developed with the help of avail literature on the issue.