Genetic syndromes, neuroconstuctivism and replicable research; challenges and future directions

Abstract

With growing awareness of problems with replicability and reproducibility within the field of genetic syndrome research, we outline why and how, as a field, we can collectively reform our practice with the goal of research improvement. We advocate that our research is of most impact when researchers investigate how developmental pathways and phenotypic profiles unfold. However, this neuroconstructivist approach and more traditional approaches bring many challenges, not least the problem of statistical power. Here, we outline the challenges to research in our field, and suggest solutions. In recognition that solutions can require substantial resource, we have also included less resource-intensive solutions where possible. The challenges and solutions discussed include sample size, individual differences, cross-disorder comparisons, multi-disciplinary expertise, measurement sensitivity and longitudinal data. Key recommendations include transparency and collaboration. For our field to produce rigorous, replicable research, researchers should strive to present protocols and data transparently (where possible) and collaborate to collect (multi-disciplinary) data as a collective effort.

Towards Reproducible and Respectful Autism Research: Combining Open and Participatory Autism Research Practices

“…Open research is both a philosophical approach (Fecher & Friesike, 2014) and a set of practices; the latter of which include, but are not limited to, the preregistration of study protocols, as well as the sharing of study materials, data, and outputs (see for example Kramer & Bosman, 2018). These practices aim to make the entire research process more transparent, reproducible, collaborative, and accessible (Allen, 2019;Asendorpf et al, 2013;Crüwell et al, 2019;Farran & Scerif, 2022;Kathawalla et al, 2021;Munafò et al, 2017;Open Science Collaboration, 2015;Pownall et al, 2021;Syed, 2019). Importantly, the principles of equity, diversity, and inclusion are central to open research (see the Open Scholarship Umbrella; Robinson, 2018;Turoman et al, 2022;Whitaker & Guest, 2020).…”

Exploring relative strengths in people with Down syndrome: Spatial thinking and its role in mathematics

“…A particular strength of this paper is our use of adequately powered statistics, supported by Bayesian statistics, where required. Studies including people with neurodiverse conditions often have small samples that limit the conclusions that can be drawn (Farran & Scerif, 2022).…”

Cross‐sectional and longitudinal assessment of cognitive development in Williams syndrome

“…When cross‐sectional data are used to plot developmental trajectories, it is not possible to differentiate individual differences from true change over time, and thus any developmental claims made using cross‐sectional data ideally require validation from longitudinal data (Thomas et al., 2009). For rare genetic syndromes such as WS, sufficiently powered sample sizes of longitudinal data are difficult to obtain (Farran, 2021; Farran & Scerif, 2022). In the current study, we present cross‐sectional and longitudinal data in the largest WS sample to‐date, drawn from the WISDOM database (https://blogs.ucl.ac.uk/wisdom/).…”