31 General Introduction 1 between-person differences in a dataset would actually be news to anyone at the university. Every statistics course I ever took (and there were many: descriptive statistics, inferential statistics, psychometrics and data analysis in the pre-masters curriculum and multivariate analysis, advanced statistics in R, mixed-effects models, and structural equation modeling during the Research Master) taught me various ways to account for such differences in the data. In regression analysis, for example, large variability around the group average automatically implies a large standard error, which reduces the significance of average effects. A statistical technique that is a bit more advanced is mixedeffects modeling, which can estimate average effects while controlling for individual variability by including random intercepts and/or random slopes. The implicit message from statistics – at least to me – was that inter- and intra-individual variance was something of a nuisance that statistically can and should be accounted for. When individual variation is filtered out, the path to making causal inferences between variables of interest (or "true effects", should they exist) is more open. Back then (and now still) I considered the pursuit of causal laws an important aim because it can produce knowledge to eventually help individuals. For example, it was nomothetic between-person research that taught the world that smoking causes lung cancer (Hill, 1965; cf. Borsboom et al., 2022) forming the basis for large-scale prevention and cessation programs which, eventually, benefit the individuals. It was with this nomothetic background that I arrived at the office of Roy Otten to discuss possibilities for a major research project. This was in 2018, at the start of my last academic study year. In preparation for that meeting, I had thought of some clever study design with which I thought I could impress. I can't really remember its details, but it of course required recruiting and analyzing a large clientele, to find out whether some kind of true effect existed. Roy grinned and told me that not only was setting up such a study unfeasible in one year within a residential care setting, but it was also not necessary. "Do a smaller number of extensive case studies, that's much more useful for clinical practice", he said. That was a stance I had not heard before, so I was surprised. It made much more sense a few weeks later when I started my major research project as an intern at the research department of the healthcare organization Pluryn. There I was co-supervised by Evelien Poelen, whose work showed that – to mental healthcare professionals and practiceoriented researchers alike – it was glaringly obvious that one size would never fit all. In practice, everyone particularly valued personalization. Each client, after all, is unique. A somewhat different take than at the university. I was lucky to be an intern at two projects on substance use, one nomothetic project
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