Collating your responses: The Round Up

About a month ago, I decided to ask the followers of Mind Waves’ Instagram account some questions and use the responses to write a series of blog posts. For each post, I posted a poll with an option to vote ‘yes’ or ‘no’. Then I posted a question box with the prompt ‘Tell me more’. I thought this was an interesting way to collect your responses because it allowed me to do some data collection using qualitative and quantitative methods. (Stay with me here!)

Every ‘yes’ or ‘no’ poll had a near unanimous result. I asked the following questions and recorded the following results:

Q. Does exercise help your mental health?
A. 100% Yes               0% No

Q. When your mental health is bad, does your relationship with food change?
A. 97% Yes                 0% No

Q. When your mental health is bad, do your relationships change?

A.  100% Yes              0% No

Seems pretty cut and dry, doesn’t it?

The answers to these polls are examples of quantitative data; data made up of counts or numbers that are collected for statistical purposes. I found the polls useful for asking basic questions and receiving clear answers, but not learning more about you all as individuals.

I feel like we’re bombarded with this type of data all the time, especially within the past 18 months. There are constantly polls and statistics in the media that seem to make sweeping claims and act as final answers to nuanced questions. The questions asked above are still useful, and it was surprising to me exactly how definitive the results were, but they don’t tell me anything about your lived experience.

For example, 100% of you said that exercise helps your mental health. That’s every single person who voted! But then when I posted the question box and gave you a chance to elaborate, your responses were all nuanced and reflected your own individual experiences. The responses you gave to my ‘tell me more’ prompt, are examples of qualitative data; data that characterises. This kind of data can be harder to read and draw clear answers from, as opposed to quantitative data- which is all about the numbers.

But that’s the tricky thing with mental health, isn’t it? It defies clear, rational thinking and cannot be squished into numbers or a one-size-fits-all box. I can ask you if your relationship with food changes when your mental health is bad, you can say yes or no, and I can record the data; but what does that tell me about your individual experience? I find it more interesting to push further, and ask you to share your thoughts in a less structured way.

One of the ways you can read quantitative data is by noticing themes and patterns, and with these question boxes, I identified an overarching theme. The three topics that I asked for responses about were diet, exercise and relationships. These are all things that have the power to help and hinder our mental health, and most of the responses on all three topics involved some level of self-blame. For example, one response to the exercise topic wrote: “the thought of exercising makes me feel so bad because I’m lazy”. Many responses to the topics directed some level of blame towards themselves for not being able to live up to their own expectations, even when they were dealing with mental health issues. After collating dozens of your responses for these blog posts I want to reiterate what I’ve been saying all along: I wish we could be kinder to ourselves.

By including quantitative data in Mind Waves’ content, it shows a commitment to your personal stories and experiences. Who better to campaign against mental health stigma than those who experience it? Although both kinds of data are important, I believe that putting lived experience at the centre of mental health campaigning is always important.

Let me know your thoughts on this series of blog posts and be sure to message me if you have any ideas for a different topic to focus on in the future. Personally, this has been my favourite blog post to write so far, so thank you for reading it!

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