qual+ intervention (pre+ post control group design)

This is always used for Data Triangulation, In other words, qualitative data are employed to explore the reason beyond the significant or non-significant difference. If there were no qualitative data, you could only compare your findings with the results of previous studies. In my opinion, studies using this design are more convincible than those using pure pre+ post control group design.

To get information on the limitations and advantages, you can search "Sequential mixed methods research". I suggest reading the following authors.

• JW Creswell
• AJ Onwuegbuzie
• A Tashakkori

thanks for the quick answer, well it seems a bit harder though, too much to read from the authors you suggested, başarılar hocam 

no its not necessary all the time, it depends on the objective of your study and the statement of the problem. But if your study is on experimental using instructional materials or in terms of teaching pedagogies, combined quantitative and qualitative researh design is the best one to be used in order to triangulate your data, it should be bac up with qualitative informations.

I think your key issue is the value that would be added by shifting from a purely quantitative study to a mixed methods design in the form QUANT --> qual. For example, if there is a significant difference in the control versus intervention groups, do you want to validate that the intervention was indeed the source of the difference? Alternatively, if there is not a significant difference, do you want to explore the limitations that kept the intervention from working?

Note that both of those strategies imply concentrating on the intervention group. The reason is that the control group basically has little to say about what changed in their lives because (presumably) nothing changed. So, you would need a strong reason for using their life stories as a "baseline" for comparison to those from the intervention group.

Well, thanks David, very helpful questions in your answer really, however, my aim was to first validate that intervention group really have the indications (problems) which results of the scales suggest. after what you said is the issue.

In both cases you suggested there is no qual before the intervention, so this is not what I wanted. I wanted to use qual for validation of the quant before and after the intervention. It is like little trust for quan and no detailed information in quant. tbh it is getting very complicated thinking of using mixed methods.

The issue of interpreting mixed data is another problem that may harm the validity of the study. dont know what to do.

is it possible to interpret the intervention (therapy) as qualitative?

The most common use of a qual --> QUANT design is to develop the content of the quantitative portion of the project, in this case, the intervention. I'm not sure what to think of using it to validate a diagnosis.

Within the mixed methods community, there is a strong tendency to follow the Campbell and Stanley tradition, where a quantitative Pre-Post comparison would make such a design QUANT, regardless of how the intervention was delivered.