Happiness has become a big top in the social sciences. Many universities offer happiness courses that teach how to be happier. Many of the exercises that are being taught in these courses are not based on evidence of effectiveness. I am teaching a different course. The course is an introduction to the science of well-being. The aim of this course is to provide an overview of the empirical research on well-being.
Textbooks that cover well-being science are often written by textbook writers who are not experts on the topic. They are often pretty bad. A better alternative is the free textbook published by well-being expert Ed Diener on his free textbook site Noba publishing (link).
For my students, I wrote my own textbook. It is still a work in progress, but given the costly alternatives, I decided to make it public. As I said, it is a work in progress. I am always looking for ways to improve it and to correct it. Feel free to provide comments in the comment section or by email.
Wellbeing Science: In Search of the Good Life (Ulrich Schimmack)
The world of scientific publishing is changing rapidly and there is a growing need to share scientific information as fast and as cheap as possible.
Traditional journals with pre-publication peer-review are too slow and focussed on major ground-breaking discoveries.
Open-access journals can be expensive.
R-Index Bulletin offers a new opportunity to share results with the scientific community quickly and free of charge.
R-Index Bulletin also avoids the problems of pre-publication peer-review by moving to a post-publication peer-review process. Readers are welcome to comment on posted contributions and to post their own analyses. This process ensures that scientific disputes and their resolution are open and part of the scientific process.
For the time being, submissions can be uploaded as comments to this blog. In the future, R-Index Bulletin may develop into a free online journal.
A submission should contain a brief description of the research question (e.g., what is the R-Index of studies on X, by X, or in the journal X?), the main statistical results (median observed power, success rate, inflation rate, R-Index) and a brief discussion of the implications of the analysis. There is no page restriction and analyses of larger data sets can include moderator analysis. Inclusion of other bias tests (Egger’s regression, TIVA, P-Curve, P-Uniform) is also welcome.
If you have conducted an R-Index analysis, please submit it to R-Index Bulletin to share your findings.
Submissions can be made anonymously or with an author’s name.
Go ahead and press the “Leave a comment” or “Leave a reply” button or scroll to the bottom of the page and past your results in the “Leave a reply” box.