Research synthesis methods 

Aims and scope

Research synthesis techniques such as systematic reviews and meta-analyses have become standard methods for aggregating the results from thematically related research in psychology. They can be used to describe the state of the art in a research field, to test and/or compare theories, and to derive conclusions about the effectiveness of interventions.

The overall aim of our research is to address hotspot topics in any subfield of psychology and related areas with the aid of research synthesis methods. Furthermore, we aim to further develop research synthesis methods. The topics covered include, but are not limited to:

  • Systematic reviews and meta-analyses contributing to the recent discussion on replicability, transparency, and research integrity in psychology;
  • Meta-analytic replications and extensions of previously published syntheses, e.g., by applying more recent approaches and/or by including more recent primary studies;
  • Methodological advances in research synthesis methods relevant for any subfield of psychology;
  • Quality appraisal systems for primary, secondary, and meta-analytic studies.

Research projects

Systematic Review Automation

(together with André Bittermann, ZPID)


ForSynData - Guidelines for FAIR and reusable research syntheses in psychology and educational research

(together with Dr. Tamara Heck, DIPF)


4th Symposium on Big Data and Research Syntheses in Psychology with a special focus on Machine Learning & Open Science, 8. bis 10. Mai 2023, Trier, Germany:
Videos and presentations

Research Synthesis and Big Data in Psychology, May 17-21, 2021, online:
Videos and presentations

Research Synthesis incl. Pre-Conference Symposium: Big Data in Psychology, May 27-31, 2019, Dubrovnik, Croatia:
Videos and presentations

Research Synthesis 2018, June 10-12, 2018, Trier, Germany:
Videos and presentations

Selected publications

Bucher, L., Burgard, T., Tran, U., Prinz, G., Bosnjak, M., & Voracek, M. (2023).

Keeping Meta-Analyses Alive and Well: A Tutorial on Implementing and Using Community-Augmented Meta-Analyses in PsychOpen CAMA.

Advances in Methods and Practices in Psychological Science, 6(4).

Burgard, T. & Bittermann, A. (2023).

Reducing Literature Screening Workload with Machine Learning. Systematic Review of Tools and their Performance.

Zeitschrift für Psychologie, 231(1), 3-15.

Seekircher, J., Burgard, T., & Bosnjak, M. (2023).

The Effects of Clinical Meditation Programs on Stress and Well-Being. An Updated Rapid Review and Meta-Analysis of Randomized Controlled Trials (RCTs) With Active Comparison Groups.

Zeitschrift für Psychologie, 231(1), 16-29.

Burgard, T., Bosnjak, M., & Studtrucker, R. (2022).

PsychOpen CAMA: Publication of Community-Augmented Meta-Analyses in Psychology.

Research Synthesis Methods, 13: 134-143.

Burgard, T., Bosnjak, M., & Studtrucker, R. (2021).

Community-augmented meta-analyses (CAMAs) in Psychology: Potentials and current systems.

Zeitschrift für Psychologie 229(1), 15-23.

Wedderhoff, N., Gnambs, T., Wedderhoff, O., Burgard, T. & Bosnjak, M. (2021).

On the structure of affect: A meta-analytic investigation of the 24 dimensionality and the cross-national applicability of the positive and negative affect schedule (PANAS).

Zeitschrift für Psychologie 229(1), 24–37.

Steinmetz, H., Bosnjak, M., & Isidor, R. (2020).

Meta-analytische Strukturgleichungsmodelle: Potenziale und Grenzen illustriert an einem Beispiel aus der Organisationspsychologie.

Psychologische Rundschau, 71(2), 111–118.

Burgard, T., Bosnjak, M., & Wedderhoff, N. (2020).

Konditionierungseffekte in Panel-Untersuchungen: Systematische Übersichtsarbeit und Meta-Analyse am Beispiel sensitiver Fragen.

Psychologische Rundschau, 71(2), 89-95.

Burgard, T., Bosnjak, M. & Wedderhoff, N. (2020).

Response rates in online surveys with affective disorder participants. A meta-analysis of study design and time effects between 2008 and 2019.

Psychologische Rundschau, 228(1), 14-24.