From clinical trials to curious conversations
I’ve spent my career navigating two very different ways of understanding human change. One prioritises rigour and generalisability; the other, personal meaning and context. In this piece, I reflect on what it might mean to hold the tension between two very different approaches in applied psychology.
Back in the days of clinical research Investigator Meetings. Sums up the vibe - this photo always makes me laugh.
When I started my career in psychology, I was a clinical researcher, helping pharmaceutical companies understand how their products were improving cognitive functioning, ability to perform everyday tasks and quality of life. Our approach was entirely quantitative — we had lots of measures that translated lived experience into neat numbers we could analyse on spreadsheets. We did all we could to protect the quality of those data (and it WAS all about the data - never once did I work directly with a patient in 20 years!). Our methodologies were designed to minimise bias, reduce inter-rater variance, harmonise translations across countries and cultures, and give the most reliable result. These approaches were well designed for the questions we were trying to answer - what’s the probability that this drug is effective in this population? Is it safe? How well does it work?
It was a fascinating change of course when I began my professional development as a Coaching Psychologist and at the same time shifted my research practice to more qualitative methods. In these disciplines, we work directly with people, rather than the numbers that try to represent them, aim to centre individual voices, understand diverse experiences and, in the case of coaching, work with clients to take an experimental approach to change - working with an N of 1, rather than the 10s, hundreds or thousands of participants involved in clinical research! Here, the questions we're seeking to answer shift: what works for this person, in this context, at this moment in time?
I think my biggest learning as I’ve moved from quantitative to inquiry-based work is how I understand subjectivity. In my early career, it was something to control for - a potential source of bias that could undermine the reliability of our data. Accuracy meant neutrality, repeatability, and statistical precision. But in coaching and evaluation, I’ve come to see subjectivity not as a problem to be solved, but as essential source of insight. A client’s individual and unique experience, isn’t noise in the data - it is the data! In these contexts, the idea of accuracy changes . It’s no longer about stripping away personal meaning to get to a generalisable answer; it’s about staying attuned to what matters in this moment, for this individual. It’s a kind of clarity that’s experienced rather than calculated, a shift from controlling data to letting it naturally unfold.
Two very different approaches then - the first focussing on understanding what reliably works across a population, and the second is focussed on what works for this person, in this specific context. Both are valid approaches, but they aren't interchangeable. Problems arise when we apply the logic of one to the other - for example, when we expect individual stories to produce statistically generalisable outcomes, or when we reduce complex human experiences to a single score. Asking the right question means understanding not just the method, but the intention behind it.
Looking back, I see my professional journey not just as a change in roles, but as a deepening appreciation for different ways of knowing. Both quantitative research and inquiry-based methods strive to make sense of human experience, but they do so through different lenses, guided by different questions. The risk lies in collapsing one into the other, in mistaking population-level patterns for personal truths, or elevating individual experiences to the status of universal evidence. What I’ve learned is that clarity comes not only from choosing the right method, but from asking judicious questions that fit the context. And sometimes, it also means being willing to sit with ambiguity - to work in the messiness, rather than try to tidy it away.
I suppose my greatest learning (having once been a true devotee to the RCT!) is that meaningful insight often emerges not from control, but from curiosity and responsiveness. Respecting those boundaries, and the unique insights each approach offers, allows us to work with both robustness and real-world fit, whether we’re analysing outcomes on a spreadsheet or sitting across from a client who is making sense of a personal challenge the very first time.
