Leapfrog Information and Resources
Leapfrog Trial Information and Resources
Background
The motivation for developing the leapfrog design was to have a version of a bayesian adaptive platform trial design that would be relatively accessible and simple to use for researchers in clinical psychology (see Blackwell et al., 2019). In recent years the use of adaptive platform trials in mental health treatment development has been increasingly advocated (e.g., Gold et al., 2022). This is largely a consequence of their prominent use for treatment/vaccine development during the COVID pandemic (Calfee et al., 2022). However, at the time we started developing the leapfrog design (ca. early 2017) there was less literature available on adaptive platform designs. Further, what literature there was tended to use complex Bayesian analyses and focus on futility testing (i.e., screening new treatments against an existing one, dropping those that were ineffective). With the leapfrog design we hoped to make planning and running such a trial simpler by demonstrating that it could be done with (relatively) simple analyses based on Bayes factors (building on work by Schönbrodt et al., 2017). We also aimed to go beyond futility testing by introducing a simple method for identifying effective treatments and “promoting” them to become the new control condition. This provides a mechanism for ongoing continuous treatment optimization and allows implementation of a “perpetual trial”. While previous literature had hinted that something along these lines might be possible they had not specified a method for doing so (e.g., Hobbs et al., 2018). We chose the term “leapfrog” design to reflect the way effective treatments would “leapfrog” over each other to become the new control condition, the new benchmark that other treatments would now have to beat.
Further reading and resources
Leapfrog Design:
Here are some introductory exercises I made to help familiarise people with the design and simulating sequential Bayes factors.
Description of the rationale for using adaptive platform designs in mental health treatment development, and introduction of the leapfrog design as a simple means to do this:
Blackwell, S. E., Woud, M. L., Margraf, J., & Schönbrodt, F. D. (2019). Introducing the leapfrog design: A simple Bayesian adaptive rolling trial design for accelerated treatment development and optimization. Clinical Psychological Science, 7(6), 1222–1243. https://doi.org/10.1177/2167702619858071
A demonstration leapfrog trial, applying the design to an internet-delivered cognitive training intervention to reduce anhedonia. This aimed to demonstrate not only the design, but also illustrate how various technical aspects (e.g. complex trial planning, pre-registration, randomization) could be implemented via linked resources available on the Open Science Framework:
Blackwell, S. E., Schönbrodt, F. D., Woud, M. L., Wannemüller, A., Bektas, B., Rodrigues, M. B., Hirdes, J., Stumpp, M., & Margraf, J. (2023). Demonstration of a ‘leapfrog’ randomized controlled trial as a method to accelerate the development and optimization of psychological interventions. Psychological Medicine, 53, 6113–6123. https://doi.org/10.1017/ S0033291722003294
This paper discusses the potential for implementing the leapfrog design in routine practice, for example for treatment personalization research:
Blackwell, S. E. (2024). Using the ‘Leapfrog’ Design as a Simple Form of Adaptive Platform Trial to Develop, Test, and Implement Treatment Personalization Methods in Routine Practice. Administration and Policy in Mental Health and Mental Health Services Research. https://doi.org/10.1007/s10488-023-01340-4
Some of these ideas had previously been summarized in this paper:
Deisenhofer, A.-K., Barkham, M., Beierl, E. T., Schwartz, B., Aafjes-van Doorn, K., Beevers, C. G., Berwian, I. M., Blackwell, S. E., Bockting, C. L., Brakemeier, E.-L., Brown, G., Buckman, J. E. J., Castonguay, L. G., Cusack, C. E., Dalgleish, T., de Jong, K., Delgadillo, J., DeRubeis, R. J., Driessen, E., … Cohen, Z. D. (2024). Implementing precision methods in personalizing psychological therapies: Barriers and possible ways forward. Behaviour Research and Therapy, 172, 104443. https://doi.org/10.1016/j.brat.2023.104443
You can also find a presentation on the leapfrog design I gave online in the “Person-Centered Treatment Prevention Collaborative” resource library here: https://osf.io/wcqpt/ (amongst many other really excellent presentations by others!)
Sequential Bayesian Analyses
These papers provide a good introduction to Bayes factors and sequential Bayesian analyses, as well as introducing an R package to facilitate this:
Schönbrodt, F. D., & Wagenmakers, E.-J. (2018). Bayes factor design analysis: Planning for compelling evidence. Psychonomic Bulletin & Review, 25(1), 128–142. https://doi.org/10.3758/s13423-017-1230-y
Schönbrodt, F. D., Wagenmakers, E.-J., Zehetleitner, M., & Perugini, M. (2017). Sequential hypothesis testing with Bayes factors: Efficiently testing mean differences. Psychological Methods, 22(2), 322–339. https://doi.org/10.1037/met0000061
Stefan, A. M., Gronau, Q. F., Schönbrodt, F. D., & Wagenmakers, E.-J. (2019). A tutorial on Bayes Factor Design Analysis using an informed prior. Behavior Research Methods, 51(3), 1042–1058. https://doi.org/10.3758/s13428-018-01189-8
See also this paper for a broader consideration of sequential analyses including an NHST approach:
Lakens, D. (2014). Performing high-powered studies efficiently with sequential analyses. European Journal of Social Psychology, 44(7), 701–710. https://doi.org/10.1002/ejsp.2023
This preprint illustrates a method of doing sequential analyses using effect sizes and their confidence intervals:
Blackwell, S. E. (2024, September 25). Sequential Analyses using Effect Size Confidence Intervals: A Simulation-Based Approach. https://doi.org/10.31234/osf.io/q3jc6
And this paper describes a sequential ANOVA based on a "sequential probability ratio test" (with R package included!):
Steinhilber, M., Schnuerch, M., & Schubert, A.-L. (2024). Sequential analysis of variance: Increasing efficiency of hypothesis testing. Psychological Methods. https://doi.org/10.1037/met0000677 (pre-print version here)
Other articles referred to in the text above:
Angus, D. C., Alexander, B. M., Berry, S., Buxton, M., Lewis, R., Paoloni, M., Webb, S. A. R., Arnold, S., Barker, A., Berry, D. A., Bonten, M. J. M., Brophy, M., Butler, C., Cloughesy, T. F., Derde, L. P. G., Esserman, L. J., Ferguson, R., Fiore, L., Gaffey, S. C., … The Adaptive Platform Trials Coalition. (2019). Adaptive platform trials: Definition, design, conduct and reporting considerations. Nature Reviews Drug Discovery, 18(10), Article 10. https://doi.org/10.1038/s41573-019-0034-3
Calfee, C. S., Liu, K. D., Asare, A. L., Beitler, J. R., Berger, P. A., Coleman, M. H., Crippa, A., Discacciati, A., Eklund, M., Files, D. C., Gandotra, S., Gibbs, K. W., Henderson, P., Levitt, J. E., Lu, R., Matthay, M. A., Meyer, N. J., Russell, D. W., Thomas, K. W., … Consortium contributors. (2022). Clinical trial design during and beyond the pandemic: The I-SPY COVID trial. Nature Medicine, 28(1), Article 1. https://doi.org/10.1038/s41591-021-01617-x
Gold, S. M., Bofill Roig, M., Miranda, J. J., Pariante, C., Posch, M., & Otte, C. (2022). Platform trials and the future of evaluating therapeutic behavioural interventions. Nature Reviews Psychology, 1(1), Article 1. https://doi.org/10.1038/s44159-021-00012-0
Hobbs, B. P., Chen, N., & Lee, J. J. (2018). Controlled multi-arm platform design using predictive probability. Statistical Methods in Medical Research, 27(1), 65–78. https://doi.org/10.1177/0962280215620696
Complex Trial Designs and Applications in Mental Health
I’m broadly interested in the application of more complex trial designs in the context of psychological interventions and mental health more generally, and have started collecting papers and resources here. I have tried to restrict these to examples from mental health plus a few general papers - there are more examples in the broader medical literature. Let me know if you come across something you think I could add here!
Adaptive Platform Designs
As far as I am aware, this leapfrog trial is still currently the only example of a completed adaptive platform trial in mental health treatment development - please let me know if you come across any others so I can add them:
Blackwell, S. E., Schönbrodt, F. D., Woud, M. L., Wannemüller, A., Bektas, B., Rodrigues, M. B., Hirdes, J., Stumpp, M., & Margraf, J. (2023). Demonstration of a ‘leapfrog’ randomized controlled trial as a method to accelerate the development and optimization of psychological interventions. Psychological Medicine, 53, 6113–6123. https://doi.org/10.1017/S0033291722003294
This (currently ongoing) study also uses a leapfrog design:
https://drks.de/search/de/trial/DRKS00033623
Here are some other non-mental-health or general papers on or using adaptive platform or similar trial designs:
Angus, D. C., Alexander, B. M., Berry, S., Buxton, M., Lewis, R., Paoloni, M., Webb, S. A. R., Arnold, S., Barker, A., Berry, D. A., Bonten, M. J. M., Brophy, M., Butler, C., Cloughesy, T. F., Derde, L. P. G., Esserman, L. J., Ferguson, R., Fiore, L., Gaffey, S. C., … The Adaptive Platform Trials Coalition. (2019). Adaptive platform trials: Definition, design, conduct and reporting considerations. Nature Reviews Drug Discovery, 18(10), Article 10. https://doi.org/10.1038/s41573-019-0034-3
Calfee, C. S., Liu, K. D., Asare, A. L., Beitler, J. R., Berger, P. A., Coleman, M. H., Crippa, A., Discacciati, A., Eklund, M., Files, D. C., Gandotra, S., Gibbs, K. W., Henderson, P., Levitt, J. E., Lu, R., Matthay, M. A., Meyer, N. J., Russell, D. W., Thomas, K. W., … Consortium contributors. (2022). Clinical trial design during and beyond the pandemic: The I-SPY COVID trial. Nature Medicine, 28(1), Article 1. https://doi.org/10.1038/s41591-021-01617-x
Files, D. C., Matthay, M. A., Calfee, C. S., Aggarwal, N. R., Asare, A. L., Beitler, J. R., Berger, P. A., Burnham, E. L., Cimino, G., Coleman, M. H., Crippa, A., Discacciati, A., Gandotra, S., Gibbs, K. W., Henderson, P. T., Ittner, C. A. G., Jauregui, A., Khan, K. T., Koff, J. L., … undefined. (2022). I-SPY COVID adaptive platform trial for COVID-19 acute respiratory failure: Rationale, design and operations. BMJ Open, 12(6), e060664. https://doi.org/10.1136/bmjopen-2021-060664
Hobbs, B. P., Chen, N., & Lee, J. J. (2018). Controlled multi-arm platform design using predictive probability. Statistical Methods in Medical Research, 27(1), 65–78. https://doi.org/10.1177/0962280215620696
Liu, M., Li, Q., Lin, J., Lin, Y., & Hoffman, E. (2021). Innovative trial designs and analyses for vaccine clinical development. Contemporary Clinical Trials, 100, 106225. https://doi.org/10.1016/j.cct.2020.106225
Marschner, I. C., & Schou, I. M. (2024). Analysis of Nonconcurrent Controls in Adaptive Platform Trials: Separating Randomized and Nonrandomized Information. Biometrical Journal, 66(6), e202300334. https://doi.org/10.1002/bimj.202300334
Wason, J. M. S., & Trippa, L. (2014). A comparison of Bayesian adaptive randomization and multi-stage designs for multi-arm clinical trials. Statistics in Medicine, 33(13), 2206–2221. https://doi.org/10.1002/sim.6086
Other Adaptive Bayesian Designs
This trial uses the sample principle as the leapfrog design (adaptive Bayesian design based on sequential Bayes factors), but without adding additional addition trial arms:
Ramineni, V., Millroth, P., Iyadurai, L., Jaki, T., Kingslake, J., Highfield, J., Summers, C., Bonsall, M. B., & Holmes, E. A. (2023). Treating intrusive memories after trauma in healthcare workers: A Bayesian adaptive randomised trial developing an imagery-competing task intervention. Molecular Psychiatry, 28(7), 2985–2994. https://doi.org/10.1038/s41380-023-02062-7
This ongoing trial also uses sequential Bayesian analyses with two arms:
https://drks.de/search/de/trial/DRKS00033313
SMART Design
Eberle, J. W., Daniel, K. E., Baee, S., Silverman, A. L., Lewis, E., Baglione, A. N., Werntz, A., French, N. J., Ji, J. L., Hohensee, N., Tong, X., Huband, J. M., Boukhechba, M., Funk, D. H., Barnes, L. E., & Teachman, B. A. (2024). Web-based interpretation bias training to reduce anxiety: A sequential, multiple-assignment randomized trial. Journal of Consulting and Clinical Psychology, 92(6), 367–384. https://doi.org/10.1037/ccp0000896
Nelson, B., Amminger, G. P., Yuen, H. P., Wallis, N., Kerr, M. J., Dixon, L., … McGorry, P. D. (2018). Staged Treatment in Early Psychosis: A sequential multiple assignment randomised trial of interventions for ultra high risk of psychosis patients. Early Intervention in Psychiatry, 12(3), 292–306. https://doi.org/10.1111/eip.12459
Liu, H., Chen, G., Li, J., Hao, C., Zhang, B., Bai, Y., Song, L., Chen, C., Xie, H., Liu, T., Caine, E. D., & Hou, F. (2021). Sequential multiple assignment randomised trial of a brief contact intervention for suicide risk management among discharged psychiatric patients: An implementation study protocol. BMJ Open, 11(11), e054131. https://doi.org/10.1136/bmjopen-2021-054131
Schmitz, J. M., Stotts, A. L., Vujanovic, A. A., Weaver, M. F., Yoon, J. H., Vincent, J., & Green, C. E. (2018). A sequential multiple assignment randomized trial for cocaine cessation and relapse prevention: Tailoring treatment to the individual. Contemporary Clinical Trials, 65, 109–115. https://doi.org/10.1016/j.cct.2017.12.015
Sauer-Zavala, S., Southward, M. W., Stumpp, N. E., Semcho, S. A., Hood, C. O., Garlock, A., & Urs, A. (2022). A SMART approach to personalized care: Preliminary data on how to select and sequence skills in transdiagnostic CBT. Cognitive Behaviour Therapy, 51(6), 435–455. https://doi.org/10.1080/16506073.2022.2053571
Group sequential designs
Huckvale, K., Hoon, L., Stech, E., Newby, J. M., Zheng, W. Y., Han, J., Vasa, R., Gupta, S., Barnett, S., Senadeera, M., Cameron, S., Kurniawan, S., Agarwal, A., Kupper, J. F., Asbury, J., Willie, D., Grant, A., Cutler, H., Parkinson, B., … Christensen, H. (2023). Protocol for a bandit-based response adaptive trial to evaluate the effectiveness of brief self-guided digital interventions for reducing psychological distress in university students: The Vibe Up study. BMJ Open, 13(4), e066249. https://doi.org/10.1136/bmjopen-2022-066249
Neumann, K., Grittner, U., Piper, S. K., Rex, A., Florez-Vargas, O., Karystianis, G., Schneider, A., Wellwood, I., Siegerink, B., Ioannidis, J. P. A., Kimmelman, J., & Dirnagl, U. (2017). Increasing efficiency of preclinical research by group sequential designs. PLOS Biology, 15(3), e2001307. https://doi.org/10.1371/journal.pbio.2001307
Lakens, D., Pahlke, F., & Wassmer, G. (2021). Group Sequential Designs: A Tutorial. https://doi.org/10.31234/osf.io/x4azm
Just In Time Adaptive Interventions
Coppersmith, D. D. L., Dempsey, W., Kleiman, E. M., Bentley, K. H., Murphy, S. A., & Nock, M. K. (2022). Just-in-Time Adaptive Interventions for Suicide Prevention: Promise, Challenges, and Future Directions. Psychiatry, 85(4), 317–333. https://doi.org/10.1080/00332747.2022.2092828
See also http://people.seas.harvard.edu/~samurphy/
MOST Design
Collins, L. M., Murphy, S. A., & Strecher, V. (2007). The Multiphase Optimization Strategy (MOST) and the Sequential Multiple Assignment Randomized Trial (SMART): New Methods for More Potent eHealth Interventions. American Journal of Preventive Medicine, 32(5 Suppl), S112–S118. https://doi.org/10.1016/j.amepre.2007.01.022
Collins, L. M., Nahum-Shani, I., Guastaferro, K., Strayhorn, J. C., Vanness, D. J., & Murphy, S. A. (2024). Intervention Optimization: A Paradigm Shift and Its Potential Implications for Clinical Psychology. Annual Review of Clinical Psychology, 20(Volume 20, 2024), 21–47. https://doi.org/10.1146/annurev-clinpsy-080822-051119
Watkins, E., Newbold, A., Tester-Jones, M., Javaid, M., Cadman, J., Collins, L. M., … Mostazir, M. (2016). Implementing multifactorial psychotherapy research in online virtual environments (IMPROVE-2): Study protocol for a phase III trial of the MOST randomized component selection method for internet cognitive-behavioural therapy for depression. BMC Psychiatry, 16(1), 345. https://doi.org/10.1186/s12888-016-1054-8
Watkins, E., Newbold, A., Tester-Jones, M., Collins, L. M., & Mostazir, M. (2023). Investigation of Active Ingredients Within Internet-Delivered Cognitive Behavioral Therapy for Depression: A Randomized Optimization Trial. JAMA Psychiatry, 80(9), 942–951. https://doi.org/10.1001/jamapsychiatry.2023.1937
Uwatoko, T., Luo, Y., Sakata, M., Kobayashi, D., Sakagami, Y., Takemoto, K., Collins, L. M., Watkins, E., Hollon, S. D., Wason, J., Noma, H., Horikoshi, M., Kawamura, T., Iwami, T., & Furukawa, T. A. (2018). Healthy Campus Trial: A multiphase optimization strategy (MOST) fully factorial trial to optimize the smartphone cognitive behavioral therapy (CBT) app for mental health promotion among university students: study protocol for a randomized controlled trial. Trials, 19(1), 353. https://doi.org/10.1186/s13063-018-2719-z
Master protocols:
"Master protocol" is the overarching term for the family of trial designs including adaptive platform trials, umbrella trials, basket trials and others - these papers provide a nice overview of the overarching idea and different kinds of designs:
Park, J. J. H., Siden, E., Zoratti, M. J., Dron, L., Harari, O., Singer, J., Lester, R. T., Thorlund, K., & Mills, E. J. (2019). Systematic review of basket trials, umbrella trials, and platform trials: A landscape analysis of master protocols. Trials, 20(1), 572. https://doi.org/10.1186/s13063-019-3664-1
Meyer, E. L., Mesenbrink, P., Dunger-Baldauf, C., Fülle, H.-J., Glimm, E., Li, Y., Posch, M., & König, F. (2020). The Evolution of Master Protocol Clinical Trial Designs: A Systematic Literature Review. Clinical Therapeutics, 42(7), 1330–1360. https://doi.org/10.1016/j.clinthera.2020.05.010
Woodcock, J., & LaVange, L. M. (2017). Master Protocols to Study Multiple Therapies, Multiple Diseases, or Both. New England Journal of Medicine, 377(1), 62–70. https://doi.org/10.1056/NEJMra1510062
Basket trial:
Not mental health, but I couldn't find any mental health examples:
Coyle, C., Cafferty, F. H., Rowley, S., MacKenzie, M., Berkman, L., Gupta, S., Pramesh, C. S., Gilbert, D., Kynaston, H., Cameron, D., Wilson, R. H., Ring, A., & Langley, R. E. (2016). ADD-ASPIRIN: A phase III, double-blind, placebo controlled, randomised trial assessing the effects of aspirin on disease recurrence and survival after primary therapy in common non-metastatic solid tumours. Contemporary Clinical Trials, 51, 56–64. https://doi.org/10.1016/j.cct.2016.10.004
This paper does at least discuss the concept though:
Joshi, Y. B., & Light, G. A. (2018). Using EEG-Guided Basket and Umbrella Trials in Psychiatry: A Precision Medicine Approach for Cognitive Impairment in Schizophrenia. Frontiers in Psychiatry, 9. https://doi.org/10.3389/fpsyt.2018.00554
Umbrella trial:
Hutton, P., Kelly, J., Taylor, C. D. J., Williams, B., Emsley, R., Alexander, C. H., Vikram, A., Saddington, D., McCann, A., Burke, J., Eliasson, E., Harper, S., Karatzias, T., Taylor, P. J., Watson, A., Dougall, N., Stavert, J., O’Rourke, S., Glasgow, A., … Woodrow, A. (2023). Accelerating the development of a psychological intervention to restore treatment decision-making capacity in patients with schizophrenia-spectrum disorder: A study protocol for a multi-site, assessor-blinded, pilot Umbrella trial (the DEC:IDES trial). Pilot and Feasibility Studies, 9(1), 117. https://doi.org/10.1186/s40814-023-01323-0
Nested-Precision RCT:
Kappelmann, N., Müller-Myhsok, B., & Kopf-Beck, J. (2021). Adapting the randomised controlled trial (RCT) for precision medicine: Introducing the nested-precision RCT (npRCT). Trials, 22(1), 13. https://doi.org/10.1186/s13063-020-04965-0
Trials within Cohorts (TWiCs)
Derksen, J. W. G., May, A. M., & Koopman, M. (2019). The era of alternative designs to connect randomized clinical trials and real-world data. Nature Reviews Clinical Oncology, 16(9), Article 9. https://doi.org/10.1038/s41571-019-0250-0
Kwakkenbos, L., Jewett, L. R., Baron, M., Bartlett, S. J., Furst, D., Gottesman, K., Khanna, D., Malcarne, V. L., Mayes, M. D., Mouthon, L., Poiraudeau, S., Sauve, M., Nielson, W. R., Poole, J. L., Assassi, S., Boutron, I., Ells, C., Ende, C. H. van den, Hudson, M., … Thombs, B. D. (2013). The Scleroderma Patient-centered Intervention Network (SPIN) Cohort: Protocol for a cohort multiple randomised controlled trial (cmRCT) design to support trials of psychosocial and rehabilitation interventions in a rare disease context. BMJ Open, 3(8), e003563. https://doi.org/10.1136/bmjopen-2013-003563
Relton, C., Torgerson, D., O’Cathain, A., & Nicholl, J. (2010). Rethinking pragmatic randomised controlled trials: Introducing the “cohort multiple randomised controlled trial” design. BMJ, 340, c1066. https://doi.org/10.1136/bmj.c1066
van der Velden, J. M., Verkooijen, H. M., Young-Afat, D. A., Burbach, J. P., van Vulpen, M., Relton, C., van Gils, C. H., May, A. M., & Groenwold, R. H. (2017). The cohort multiple randomized controlled trial design: A valid and efficient alternative to pragmatic trials? International Journal of Epidemiology, 46(1), 96–102. https://doi.org/10.1093/ije/dyw050
Cluster randomized and stepped wedge trials:
Barker, D., D’Este, C., Campbell, M. J., & McElduff, P. (2017). Minimum number of clusters and comparison of analysis methods for cross sectional stepped wedge cluster randomised trials with binary outcomes: A simulation study. Trials, 18(1), 119. https://doi.org/10.1186/s13063-017-1862-2
Hemming, K., Eldridge, S., Forbes, G., Weijer, C., & Taljaard, M. (2017). How to design efficient cluster randomised trials. BMJ, 358, j3064. https://doi.org/10.1136/bmj.j3064
Cook, A. J., Delong, E., Murray, D. M., Vollmer, W. M., & Heagerty, P. J. (2016). Statistical lessons learned for designing cluster randomized pragmatic clinical trials from the NIH Health Care Systems Collaboratory Biostatistics and Design Core. Clinical Trials (London, England), 13(5), 504–512. https://doi.org/10.1177/1740774516646578
Kuyken, W., Ball, S., Crane, C., Ganguli, P., Jones, B., Montero-Marin, J., Nuthall, E., Raja, A., Taylor, L., Tudor, K., Viner, R. M., Allwood, M., Aukland, L., Dunning, D., Casey, T., Dalrymple, N., Wilde, K. D., Farley, E.-R., Harper, J., … Williams, J. M. G. (2022). Effectiveness and cost-effectiveness of universal school-based mindfulness training compared with normal school provision in reducing risk of mental health problems and promoting well-being in adolescence: The MYRIAD cluster randomised controlled trial. Evidence-Based Mental Health, 25(3), 99–109. https://doi.org/10.1136/ebmental-2021-300396
Dorsey, S., Gray, C. L., Wasonga, A. I., Amanya, C., Weiner, B. J., Belden, C. M., Martin, P., Meza, R. D., Weinhold, A. K., Soi, C., Murray, L. K., Lucid, L., Turner, E. L., Mildon, R., & Whetten, K. (2020). Advancing successful implementation of task-shifted mental health care in low-resource settings (BASIC): Protocol for a stepped wedge cluster randomized trial. BMC Psychiatry, 20(1), 10. https://doi.org/10.1186/s12888-019-2364-4
Wellek, S., Donner-Banzhoff, N., König, J., Mildenberger, P., & Blettner, M. (2019). Planning and Analysis of Trials Using a Stepped Wedge Design: Part 26 of a Series on Evaluation of Scientific Publications. Deutsches Ärzteblatt international. https://doi.org/10.3238/arztebl.2019.0453