This sixth collection of "Hotspots in Psychology" goes beyond presenting state-of-the-art systematic reviews and meta-analyses in research fields to also discuss the fruitfulness and challenges of using big data in psychological research. For instance, topics such as intensive longitudinal data (e.g., time series and experience sampling), nonobtrusive methods of data gathering (e.g., sensors and log data), and how big data can be handledand analyzed.

Five contributions explore the application of individual participants meta-analyses as a way to replicate studies, the role of the degree of anthropomorphism ("humanlikeness") in human-robot interactions, the challenge of multiple dependent effect sizes when conducting a meta-analytical structural equation model, the value of using log data from online platforms as a way to predict learning outcomes, and the utility of a blockwise fit evaluation in structural equation models with many longitudinally measured variables. To promote open science, supplemental material is available in a repository.