Cognitive Rehabilitation Following Mild Traumatic Brain Injury using Hypnotic Suggestion

Introduction: Cost-effective rehabilitation of persistent cognitive problems following Mild Traumatic Brain Injury (MTBI) remains elusive. Method: Here, we extend previous findings on hypnotic suggestion for neurological patient groups by administering it to 22 participants suffering from persistent reduced vocational performance following MTBI. Results: Following eight weekly 1-hour treatments, we observed large effects on the Mental Fatigue Scale and Digit Span. There were medium-sized effects on the Hospital Anxiety and Depression Scale, but no effect on the Trail Making Test. Effect sizes were larger for participants with no ongoing litigation. Conclusion: In terms of effectiveness, the results compare well to conventional treatments for MTBI. We discuss limitations and propose avenues for future research

Computer-based cognitive rehabilitation following acquired brain injury: does the evidence support the claims?

This is the data used for review and meta-analysis in the paper by Lindeløv. It simply contains the spreadsheet below and an R script to run the analysis, create the figures etc. The spreadsheet has multiple sheets and comments in many cells. If you have any comments or criticism, please do not hesitate to contact me

mcp: An R Package for Regression With Multiple Change Points

The R package mcp does flexible and informed Bayesian regression with change points. mcp can infer the location of changes between regression models on means, variances, autocorrelation structure, and any combination of these. Prior and posterior samples and summaries are returned for all parameters and a rich set of plotting options is available. Bayes Factors can be computed via Savage-Dickey density ratio and posterior contrasts. Cross-validation can be used for more general model comparison. mcp ships with sensible defaults, including priors, but the user can override them to get finer control of the models and outputs. The strengths and limitations of mcp are discussed in relation to existing change point packages in R