✍️ Emily Williams, May 2026
⏱️ 7-minute read | 📚 31 linked resources (NN/g, NHS Blog, Reddit and more)
At the moment, I have a hybrid identity. I’m a Psychology and User Researcher. Pre-2022, I was an academic Psychology Researcher, before accidentally conducting what I know now as discovery surveys, observational prototype testing, expert co-design, and end-of-use evaluation around Turbo Typing. Later in 2026, I hope to be a User Researcher by title, transitioning into the public or private sector to apply my decade+ of cognitive, educational, and health psychology expertise to making products and services more user-friendly.
I'd like to reflect on two texts that have made an impact on me during this journey, on the “Deadly Sins” of Psychology and User Experience (UX) research. I've come up with four cross-disciplinary tips for best practice based on a synthesis of these sins and the authors’ solutions. See the Appendix at the bottom to read these tips in a handy shareable image.
Throughout my Psychology career, I've been a strong advocate for Open Science practices, which include being transparent about how you conduct your research and sharing your data with others. In my transition towards UX research, I'm becoming an advocate for user perspectives in product and service design; user-centred design (UCD).
In the pursuit of these identities, I've sought out handbooks for best practice. These included Chris Chambers' The Seven Deadly Sins of Psychology in September 2017, and recently David Travis and Philip Hodgson's Think Like a UX Researcher in early May 2026. The first essay in the latter is titled The Seven Deadly Sins of UX Research, and I was intrigued to learn about the pitfalls of UX research through a familiar format.
According to Chambers, Psychology's deadly sins are Bias, Hidden Flexibility, Unreliability, Data Hoarding, Corruptibility, Internment, and Bean Counting. Travis and Hodgson list UX research’s deadly sins as Credulity, Dogmatism, Bias, Obscurantism(?!), Laziness, Vagueness, and Hubris. I provide a table in the Appendix at the bottom outlining each of these with the authors’ solutions. However, while a table of fourteen solutions is a gold mine for best practice in Psychology and UX research, it can be a bit overwhelming. I've surmised four main lessons from this comparison, detailed below, weaving in definitions of each the main concepts.
Through this synthesis, I hope to provide some recommendations for both Psychology and UX researchers, including some suggestions for cross-disciplinary borrowing.
First, Psychology's sins of Hidden Flexibility and Corruptibility, and UX's sin of Vagueness warn us of the dangers of not creating (UX) or sticking to (Psychology) a clear plan. Perhaps this is to allow us the freedom to manipulate our data (corruptibility) or selectively report our results (hidden flexibility), or to try to answer several questions at once, perhaps because we failed to do research along the way (vagueness). All of these paths to madness speak to the benefits of creating or committing to a clear research plan.
In Psychology research, this could be done through writing a pre-registration (a public, time-stamped research plan) or a Registered Report (a publication type where the intro, methods and analysis plan are peer-reviewed and locked in before starting data collection). These are likely steps too far for UX researchers, where there is less of a call for external transparency and replication. (These approaches were introduced to combat the “replication crisis”, where repeating famous studies often found worryingly different results.) Also, in Private Sector UX, the work could be proprietary or under NDA, in which case publicising detailed plans would be unsuitable.
In UX research, addressing these sins could be done through pre-defining research questions, goals and hypotheses. To land on shared research questions, Travis and Hodgson suggest giving each of the user-centred design team a set of stickie notes and asking them to write down all the questions they would ask an "all-knowing, insightful user outside the room who will answer truthfully any question”. They then suggest affinity mapping these questions into clusters and dot-voting the ones most urgent to answer. Psychologists could borrow this approach to collaboratively identify and prioritise the next plans of their research group.
Second, Psychology's sins of Bias and Hidden Flexibility, and UX's sin of Bias warn us against cherry-picking positive results. Perhaps we only report the results that were statistically significant or confirmed our existing beliefs (Psychology's bias & hidden flexibility), or we hide the finding that users don't really want/need our product or service from our senior managers (UX's bias).
In Psychology research, this can again be rectified by pre-registering studies, or by relying less on statistical significance testing and considering more of a graded evidence approach like Bayesian inference. In UX research, the pre-occupation with statistical significance is less widespread. The Perceptual UX Lab take a Cognitive Psychology approach to solving UX problems, and advocate for the use of statistical and Bayesian reasoning in UX, while some UX researchers prefer to focus on practical significance rather than statistical significance.
In UX research, cherry-picking is remedied by helping the user-centred design team and senior stakeholders understand the true data, rather than telling them what they want to hear. This can involve bringing them along for the ride (see their #6), rather than waiting for a big reveal. If you do indeed find your product or service is undesired, there are diplomatic ways to break this to your team. In Psychology research, inviting principal investigators to your research sessions is unwieldy, but these tips may be helpful when discussing negative results with your team.