Neuroscience, working on shared representations between first-hand and empathy for pain
computational social science and causal inference
Mental Health prevention, eating disorders, epidemiology, e-mental health
Mental imagery interventions for dysphoric/depressed patients
Cognitive processes / Multinomial Processing Tree (MPT) models
decision making (cooperation, choice conflict, decision times)
Neural entrainment during early social interactions
lots of diverse random things, mostly with healthcare professionals
Adolescent mental health and risky decision making
E-mental health interventions and economic efficiency / innovative therapies for schizophrenic patients and health economy
psychological testing, college admissions, personnel selection
Mental health barriers/ help-seeking behavior

other method to reuse data 1
Aggregating multiple similar studies for a bigger sample

other data types
All kinds of data depending on the research question
Neuroimaging data (i.e. structural and functional MRI) and associated clinical data (e.g. diagnoses)

Metadata missing in existing documentation standards
In my experience, there is no overall kind of information missing, but it is rather in the details. For instances descriptions might be ambiguous, data names do not match the documentation, abbreviations are used but not explained and so on.
In general there is a lack of documentation at the concept level. The names of scales used in the data vary. We need more harmonized ontologies to increase findability of the data.