The neural determinants of age-related changes in fluid intelligence: a pre-registered, longitudinal analysis in UK Biobank [version 1; referees: 2 approved]
Rogier A. Kievit; Delia Fuhrmann; Gesa Sophia Borgeest; Ivan L. Simpson-Kent; Richard N. A. Henson · 2018 · Wellcome Open Research
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Background: Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods: In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the U
Abstract by Rogier A. Kievit; Delia Fuhrmann; Gesa Sophia Borgeest; Ivan L. Simpson-Kent; Richard N. A. Henson, Wellcome Open Research (2018) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
A Randomized Trial of Intraarterial Treatment for Acute Ischemic Stroke
Negative / Null Result ReportDuodenal Infusion of Donor Feces for Recurrent Clostridium difficile
Negative / Null Result ReportStenting versus Endarterectomy for Treatment of Carotid-Artery Stenosis
Negative / Null Result ReportEffects of Combination Lipid Therapy in Type 2 Diabetes Mellitus
Replication FailureA Randomized Trial of Bevacizumab for Newly Diagnosed Glioblastoma
Negative / Null Result ReportSpironolactone for Heart Failure with Preserved Ejection Fraction
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: DOAJ · DOI 10.12688/wellcomeopenres.14241.1