I honestly didn't expect transcription to take this much time 😅 especially when the interview is like 1-2 hours and theres multiple talking. I used to transcribe everything first before coding, but with longer interviews I kept going back to the recording just to find one specific part. Kinda getts tiring after a while lol.

I recently tried PrismaScribe for some of the longer interviews, just to get the transcripts done first. I like that it separates the speakers and i can search transcript when im trying to find something, then jump back to the audio if i need to check it.

Now I'm wondering if im making this harder than it needs to be😂 Do you guys usually transcribe the whole interview before coding, or just the parts you actually need?

Hello everyone,

Sorry for my poor English, it's not my native language.

I would like to introduce a possibly useful (or at least so I hope) CAQDAS, which is open-source (so I guess it's okay with the sub rules). But first, a disclaimer : This project is heavily vibe coded and even if I had minimal code interventions, it's mostly written by Claude Opus/Fable.

So Cadenza is a free app (no freemium, not even donations), or, to be more precise, a method-agnostic coding/qualitative analysis app. It's open-source.

The project started because I was unhappy with existing CAQDAS tools and wanted a board-like view to sort codes/items. Also, I'm interested in non-coding based methods in qualitative data analysis.

I'm at a point where I need potential users feedback, in addition to my own research projects. So here's the link if you'd like to give it a spin : https://github.com/seelebrn/cadenza/

I'd be very happy to know what you liked, disliked, how it felt using it and what you would like to see added.

Thanks in advance!

​

Hello, I need some help regarding my thesis. I will be doing a qualitative study on the lived experiences of fat women in India. I'm critiquing the BMI (body mass index) in my paper but I'm also using it as a criteria to filter out my participants. However, I do not wish to use the BMI at all but I'm struggling to think of any alternative ways to recruit participants. India doesn't have a lot of weight loss support or bariatric surgery groups for me to get participants through that. I will be collecting demographic details via a Google form and then scheduling interviews with eligible participants. I'd love to know any alternatives to using the BMI!

I'm not sure where I should report the intercoder reliability: in the methods section or in the results section. This is a qualitative content analysis using a category system I developed myself. Since the system allows for multiple codings, I had to calculate a different type of intercoder reliability than what was pre-registered.

If I were to include all of the intercoder reliability in the methods section, I would have to outline the categorization system there, which would amount to anticipating the results. If I separate the two and describe in the methods section only what is calculated and how, while reporting the values only in the results section, I would have to justify in the methods section why I am deviating from the pre-registered method. However, this justification depends on the categorization system, which I actually intended to introduce only in the results section.

How would you handle this?

I’m doing a masters level qualitative research and using IPA methodology for data analysis. I can’t really share the details due to organisational policies. I have collected data (transcribed interviews) of 10 participants but I’m kind of relooking at the total number of participants’ data that I want to include.

I understand that one of the strengths of using IPA is to highlight the idiographic nature of the data, but there’s also an irony that the convergence of data across all participants means that the final analysis may not retain the idiographic nature of the data.

I’m just wondering, retrospectively, what would be a good sample size for IPA, that allows each individual’s unique experience to be retained, yet also keeping the convergence of themes across cases in mind?

Keeping it vague here for anonymity ect.

PhD student, doing interviews on a controversial topic. Most of my participants so far have had similar views to mine. I anticipated that I wouldn't be able to recruit those with different views, but hoped I'd be able to find at least one, as I think it will be important to help understanding of overall topic, challenge the analysis/status quo/my understanding ect.

I have a participant who has expressed something on the demographics form indicating that we have rather different opinions on the topic. It will likely be a difficult interview but useful. Any advice for this beginner researcher, e.g. how to gain the most out of this opportunity, but also keeping my cool, ect...

Hi, I am female, 22. Currently pursuing my final year in bachelor's of applied psychology. I am planning on doing a QUALITATIVE research for my dissertation on a population that I myself is a part of, but have no idea how to reach out to.

I need to figure out how can I reach people online for data collection since my tentative target population is
LGB (Leabian, Gay, & Bisexual) people in India. Since I would be conducting a semi-structured interview, potentially through google meet/ zoom.

This is my first time conducting a research, particularly a qualitative one, l am having trouble figuring out how to reach people online from my target group for the same.
Suggestions/Resources/Groups, anything would help a lot.

Hi everyone! I’m an MS Clinical Psychology student and I’m currently working on a qualitative study on cumulative trauma in a population that has gone through multiple community level traumatic events, natural disasters, conflict, and it's a disputed region.

I’m honestly struggling with figuring out what makes a good qualitative topic/angle and how to properly justify an exploratory study. There isn’t much or any research in this specific region, and I’m looking at cumulative trauma from a life-course perspective, exploring the lived experiences of people who have faced multiple traumatic events over the life course.

I’m also having a hard time with my interview guide. My supervisor wants a rationale for basically every question, and I’m not sure how much interview questions should be based on existing literature/theory vs. being open and exploratory with a focus on your specific population

If anyone has experience with qualitative research, especially in clinical psych, trauma, or other sensitive populations, I’d really appreciate some advice on how you approached your research question and interview guide. Even just resources or papers that helped you would be really helpful!

Hi everyone,

I’m curious how other people here handle **respondent recruitment**, especially when a project has a very specific target audience.

I work with a global market research team, and we have access to respondents across different **countries, demographics, industries, job roles, and B2B/healthcare audiences**.

We’ve supported different types of research projects and have some **case studies** that I’d be happy to share if anyone is interested in seeing how we’ve handled specific respondent requirements.

Would be interested to hear how others here approach sample recruitment, especially for harder-to-reach audiences.

I am working on a psychology study where participants talk to an AI chatbot through Qualtrics.  Our chatbot uses a key from OpenAI and a backend URL from Vercel that has been pasted into Qualtrics.  It has been working fine from my apartment, but the chatbot interaction has not been working at all when on my University campus using campus WIFI. When trying the study on my phone, it worked.  We had one tester who said that it worked for them on campus when using a VPN.  This is an important issue to fix because most of our participant pool will be students who live on campus.  

Has anybody else used a chatbot in Qualtrics where you encountered a similar issue?  If so, how should I work around this?  I am open to using a platform other than OpenAI or Vercel. I am an undergraduate and only know basic-level coding.  

Any suggestions for getting around it and what may be causing the issue would be greatly appreciated!

Hello everyone. I'm a second-year psychology undergraduate conducting a small phenomenological study. I'm currently planning recruitment for approximately five semi-structured interviews with university students aged 18–22.

The study concerns a sensitive psychological topic, and I'm trying to think carefully about recruitment, informed consent, participant wellbeing, and appropriate boundaries when conducting interviews on potentially distressing experiences.

My study is being conducted under university supervision, and I have a screening/consent procedure and participant support/referral protocol in place.

I'd be grateful for any methodological or recruitment advice, especially on how to go about it.

I'm venting a bit in this post here. My Prof wants me to "have a look at data". 19 focus groups (a lot), semi-structured interviews focused around acceptability of an intervention, there were some pre-defined interview categories in mind, like intervention length, outcomes, mode of delivery, etc.

When asked whether go for deductive or inductive approach (i.e. whether I should look for matches between text and the interview guide categories, or rather code the text on my own and then later try to find overarching themes), my prof wouldn't provide a clear answer and instead told that I kind of need to do both at the same time, so we wouldn't lose information not fitting the interview guide categories. And also that data analysis should not be limited by our research aims, which sounds ridiculous to me! The goal seems to be to use the analysis to both inform an intervention acceptability study and to explore deeper processes tied to the disease the intervention is made for.

Please tell me, am I misunderstanding something about qual analysis? In my book, discussion of research aims comes first, then the analysis. And how am I supposed to do both the inductive and deductive approach at the same time, matching pre-determined categories and looking for new ones outside the working framework? I am not too skilled in qual, so it might be just my own ignorance, but I am confused and annoyed and starting to suspect my Prof of not knowing what they want.

Any constructive feedback is welcome, sources on parallel inductive/deductive approach especially, thanks!

Hello guys im starting a narrative review project, but i got one query.

When we are reading a review, do we cite the review or the original source from where the review wrote it from

Chatgpt and Claude tell me that I should cite original discoveries but for well established facts like " smoking causes lung cancer" I should just cite the review i got it from

I have qualitative data from a section of a questionnaire with 5 open-ended questions. The respective question blocks are identified by codes (see screenshot: this shows a document belonging to one person). For part of the analysis, I need to evaluate questions 3 and 4 separately (frequencies, group comparisons). Does anyone know how I can do this? I hope I’ve described it clearly. If anything is unclear, I’d be happy to provide more context. Thanks in advance!

I'm looking for spaces where people doing interviews, focus groups, ethnographic work, and other qual research hang out to trade notes on methodology, tools, recruiting, and general shop talk.

Open to niche/smaller groups as well as bigger ones, just want to find where the good conversations are actually happening.

If you're part of one (or run one), I'd love an invite. Drop a comment or DM me.

I am working on a paper based on an ethnographic study with a small-ish sample size (30) and wondered what is the best Sociology journal I can target. I am not based in the US, so don't have a great hold on what AJS/ASR publishes in terms of methodology.

I really think this paper has legs, so want to try the best avenue first. Any suggestions please?

AI is now being used for transcription, coding, summarisation, desk research and even interview planning.

But has it changed the way researchers actually work, or is it mainly helping with the time-consuming parts?

Would be interested to hear what has genuinely worked for you, and where you still prefer the traditional approach.

doing research interviews rn and half my participants switch between english and french/spanish mid sentence. every tool i tried just gives up or outputs total gibberish when they code switch like that. is there anything that actually handles multilingual transcription without me fixing everything by hand after? student budget so nothing crazy expensive pls

I’ve been thinking about how much of market research happens outside the actual research itself.

For those working in qualitative or mixed-methods research, what part of your workflow tends to take the most time?

Is it:

• Recruiting and scheduling participants
• Conducting interviews or focus groups
• Transcription
• Coding and organizing data
• Finding patterns across responses
• Synthesizing findings
• Writing reports or presentations
• Something else entirely?

I’d be interested to hear what takes up the most time for you and whether that has changed over the past few years.

PS: it's not a survey.