Register now

26 October 2018 09:00Karolinska University Hospital


Small is beautiful

"Single-case experimentation enhancing the scientist practitioner challenge"

Generally the multicenter RCT is considered the gold standard to study the effects and mechanisms of complex treatments in heterogeneous groups, using standardized instruments. The question is to what extent the results of this large-scale studies are useful for individual care recipient and provider. After all, RCT's can determine the "average" outcome for a given outcome variable, but usually are not able to determine the functional relationships between a treatment and observed change for one individual.

Fortunately, there is an efficient and robust alternative. Single-case experimental designs (SCED or N = 1 RCT's) are randomized designs in which a single unit (eg. The client, the class ...) is repeatedly observed for a predetermined period of time under various levels of at least one manipulated variable (eg. the therapy). SCED have played an important role in the development of new interventions in the field of medicine, neuropsychology, clinical and health psychology. They are not only flexible, but also relatively easy to implement in the practice of health care and they elegantly bridge the gap between research and practice. SCED offer continuous feedback on the progress of a person or a group, and the results are available in "real time". There is adequate and appropriate software available to visualize the progress during an intervention, and there are statistical tools to determine the effects and its size.

This symposium brings together a number of experts in the field, and provide a brief history of the SCED's, their essential characteristics, design requirements, visual and statistical analysis possibilities, and a number of illustrative examples from clinical research.

All you need to know

Payment: Senior researcher fee 100 €, trainee researcher fee (post doc, doctoral- and master students) 50 €

Register here to receive billing information. Sign up is complete when payment is made. 

Venue: Sune Bergströms aula, Nya Karolinska (J3:07:Sune)


09:50 - 10:00 Welcome
(Rikard Wicksell)
10:00 – 10:20 Introduction: why single case experiments?
(Johan Vlayen)
10:25 – 11:05 Visual analysis of N=1 data
(Steven Linton)
11:05 – 11:15 LEG STRETCHER
11:20 – 12:00 Statistical analyses of N=1
(Patrick Onghena)
12:00 – 13:30 LUNCH & POSTER SESSION
13:30 – 14:10 Guidelines for conducting N=1 trials
(Sunita Vohra)
14:15 – 14:55 Experience sample methods
(Falko Sniehotta)
15:00 – 15:40 Single-case reporting guideline in behavioral interventions
(Robyn Tate)
15:40 – 16:00 COFFEE BREAK
16:00 – 16:30 Panel discussion with Q&A
(All speakers)
16:30 – 16:45 Conclusions and looking forward
(Johan Vlayen & Rikard Wicksell)
17:00 – 19:00 “AFTER CONFERENCE” MINGLE (Haga Bottega, Elite Hotel Carolina Tower)
*Open to all participants at own cost

Practical information to all registered attendees:

An email with practical information has been sent to you (on Friday October 19) it seems that some of you have not received it - please check your mailbox that it has not been put in the bin or as spam. 

Here is a roundup of information to help you get ready. The conference is held at venue Sune Bergströms Aula, Nya Karolinska (J3:07:Sune) (Address: Eugeniavägen 3). Registration desk opens at 09:00 and first speaker is up at 09:50 – we run a tight schedule so please be on time. Posters should be mounted between 09:00-09:50, needles are available at the registration desk. 

There are some small changes in the program as we have made room for a panel discussion with Q&A at the end of the day. To be able to fit this in to the busy schedule the lunch break is slightly shorted. For detailed schedule please see above. 

If you have chosen invoice as payment method but not yet received the invoice – don’t worry, we will send the last invoices last week of October – as long as you have provided us with your invoice information you are all set for now.

Finally we would like to invite you to the “After conference mingle” held at Elite Hotel Carolina Tower, restaurant Haga Bottega, 17:00-19:00. Take the opportunity to mingle with the speakers, organizers and all the other attendees with a special interest in single-case experimental design. You will have the opportunity to buy drinks in the bar, and the restaurant downstairs will be open for those who want to continue the evening after the mingle. If you are planning on joining the mingle, please mention this at the registration desk when you register, so we can give the restaurant a heads up on the number of guests.  

The official hashtag for the event is #N1STHLM18, twitter away and spread the word of single case experimental design!

See you on Friday,

The conference committee


  • Raise interest in single-case research
  • Help bridge Scientist-Practitioner gap
  • Summarize state of the art for interested clinicians + applied researchers
  • Create a network on N=1 design users

Postersession: Submit posters to the N=1 Stockholm symposium

Posters will be displayed all day, and presented by the authors during the 1,5 hour lunch break/poster session. 

The purpose of the poster session is primarily to facilitate discussions among conference attendants. 

Please note that also posters presented at previous conferences will be accepted, as well as posters based on data from already published studies.

The poster should be within 80 w x 120 h (cm). 

Submit a poster abstract (or complete poster) via email to:

Register now


Sunita Vohra (Canada)
Adjunct Professor

What are N-of-1 trials and when can they be used?

N-of-1 trials are multiple crossover trials (ABAB) which are used to determine individualized treatment effects. This design offers the methodological safeguards provided by RCTs (blinding, randomization, controls, formal outcome assessment), yet avoids the some of the disadvantages of parallel group trials such as recruitment issues and lack of external validity. N-of-1 trials represent an innovation in clinical trial methods by offering a patient-centered approach to rigorously evaluate treatment options and provide individualized estimates of treatment effect so patients may participate as equal partners in informed shared decision-making about their care.

The University of Alberta has some of the world's leading scholars in the area of N-of-1 trials. We have led and contributed to a number of initiatives in the design, analysis, and reporting of N-of-1 trials, including CONSORT Extension for N-of-1 Trials (CENT) guidelines: A consensus-based standard for reporting N-of-1 trials was developed by our team in response to the large amount of variability in the quality of reporting of published N-of-1 trials.

The relevance of N-of-1 trials to personalized medicine and big data 

In an era of personalized and precision medicine, and patient-centered research, N-of-1 trials are experiencing a renaissance. They represent the intersection of research and clinical care, where the needs of the individual patient are met through the development and application of an evidence-based approach. Moreover, with the advent of big data, N-of-1 trials present a unique opportunity, by harnessing the data they generate in order to create predictive models to assist in more precise treatment plans. A database of N-of-1 trial results, whether conducted for clinical care or research, to determine which prognostic factors match with the most successful treatment option, may result in improved, personalized, patient care.

Sunita Vohra (Canada)

I am a clinician scientist with a strong interest in patient safety and evidence-based approaches to therapeutics in children. Our research program evaluates the safety and effectiveness of complementary and alternative medicine, and initiates methodological research to help answer clinically relevant questions.


  • clinical epidemiology
  • complementary and alternative medicine
  • natural health products
  • patient safety
  • pediatrics
  • randomized controlled trials
  • systematic reviews
  • N-of-1 trials

Read more

Steven J. Linton (Sweden)

WHAT YOU SEE IS WHAT YOU GET! Visual Analysis of Single Case Data

Analyzing the data from investigations using single-subject methodology can be challenging. How can we be certain that a given result is actually “significant”? In this talk I will summarize how this task can be approached based on visual analyses of graphically presented data. In this approach, the results are made transparent so each reader can assess them. Historically, single-subject methodology has relied on conducting studies that have sufficient impact so that the results can be graphically observed and the size of the effect agreed upon by viewers. I will outline methods to maximize observable outcomes when designing a single-subject study by focusing on choice of primary outcomes, baseline observations, and the selection of the intervention. Subsequently, I will provide simple strategies for enhancing the graphic presentation of data to augment the analysis. I will contend that visual analysis may be superior to more complicated statistical methods because it puts focus on the conditions needed to show a clinically significant effect. Finally, I will argue that results do not get “better” by statistical procedures, but rather by designing better studies. Fortunately, the pliability of single-case studies allows for developing procedures over time to improve outcome and its observability.

Steven J. Linton (Sweden)

Steven J. Linton is professor of Clinical Psychology and the director of the Center for Health and Medical Psychology (CHAMP). He is also active in teaching in the clinical and doctoral programs.

Current research interests are:

  • Early identification and treatment of back pain
  • Mechanisms driving pain chronicity
  • Early interventions to enhance good sleeping patterns in youth
  • The role of context in chronic pain
  • Treating comorbid chronic pain and depression
  • Pain associated with sex
  • communication between health providers and patients

Read more

Falko Sniehotta (UK)

N-of-1 Applications to Behavioural Medicine

Health behavior research has traditionally been dominated by between-subject designs. However, there are various limitations in using evidence from between-subject designs to test theoretical hypotheses about mechanisms or assign treatments to individuals. 

Quantitative single-case (N-of-1) designs based on repeated observations of a single participant are increasingly recognised as powerful tools to test theory and interventions at the individual level.  This makes them a potentially efficient mechanism for making and evaluating individualized evidence-based treatment decisions in behavioural medicine.  

The talk provides a conceptual, methodological and empirical overview of N-of-1 studies applied to behavior change.  It highlights recent examples of observational and interventional studies in the areas of physical activity, weight management and research with individuals with very rare genetic conditions. The role of experience sampling methods will be discussed and illustrated. Case examples of using N-of-1 data for mixed method studies and intervention development will be presented.  In an age of ubiquitous ambulant assessment devices, apps and accelerometers, N-of-1 methods have the potential to generate new behavior change approaches in public health and chronic disease management which can be optimized to meet the needs of individuals.

Falko Sniehotta (UK)

I am a behavioural scientist. My research programme aims at developing and testing a) interventions to change behaviours relevant to health and health care, b) theory of behaviour change and c) research methods for behavioural research. The research portfolio includes studies with patients, health care professionals and members of the public. This research is conducted with my colleages in the IHS, the Newcastle Health Psychology Group and colleages nationally and internationally.  Our research is translational, multi-methodological and multidisciplinary.

Read more

Robyn Tate (Australia)

Striving for Level 1 evidence in the conduct and report of single-case experimental designs

In 2011, the Oxford Centre for Evidence-Based Medicine released Levels of Evidence 2. In this hierarchy of evidence, the randomised N-of-1 trial was classified as providing Level I evidence for treatment decision purposes in the individual patient/client, as well as for the identification of harms. Until that break-through, single-case methodology, irrespective of its scientific quality, was generally classified as providing a low level of evidence (viz., Level/ClassIII), and it continues to be so classified by some influential evidence hierarchies (e.g., American Academy of Neurology; Australian National Health and Medical Research Council). Critical appraisal of published reports in the behavioural sciences using single-case methodology reveals the spectrum of scientific quality, ranging from those studies (the minority) that arguably furnish Level 1 evidence through to those (the majority) providing a low level of evidence. Recent efforts in the behavioural sciences, and particularly the neurorehabilitation field, has built on work in the areas of clinical psychology and special education to develop resources for planning, implementing and reporting scientifically rigorous single-case experiments. The presentation describes two such instruments: a reporting guideline (Single-Case Reporting guideline In BEhavioural interventions (SCRIBE)) and a critical appraisal scale (Risk of Bias in N-of-1 Trials (RoBiNT) Scale). These tools are complementary in that a reporting guideline makes recommendations about what should be reported (i.e., what was done), whereas a critical appraisal scale evaluates the scientific quality of what was done (i.e., how well it was done). These and similar instruments will assist clinicians and researchers using single-case methods to conduct and report their work at a high standard.

Robyn Tate (Australia)

Professor Robyn Tate is a clinical psychologist and neuropsychologist with extensive clinical experience in rehabilitation after traumatic brain injury. Her initial clinical appointment was at the Brain Injury Rehabilitation Service, Lidcombe Hospital, Sydney, Australia where she was involved in the development and delivery of clinical services over a 15-year period.

She was then appointed Senior Lecturer in the Department of Psychology at the University of Sydney where she worked for 7 years, teaching graduate students courses in neuropsychological assessment and rehabilitation. Robyn's current appointment is Professorial Research Fellow at the Rehabilitation Studies Unit, Sydney Medical School, University of Sydney, where she has worked for the past 11 years.

Read more

Patrick Onghena (Belgium)

Forcing round pegs into round holes: The statistical analysis of single-case experimental data

More than 40 years ago, Donald Hartmann wrote his influential pamphlet on “Forcing square pegs into round holes: Some comments on ‘an analysis-of-variance model for the intrasubject replication design’. In that pamphlet, Hartmann criticized the use of naive ANOVA models for the analysis of single-case experimental data, but he also indicated the alternative direction in which the statistical analysis of single-case experimental data had to go. In our presentation we will discuss the present state of affairs of this alternative direction. We will make a sharp distinction between descriptive statistics and inferential statistics, and we will present a fourfold classification of inferential statistics
following two orthogonal dichotomies: design-based versus model-based inference, and unilevel versus multilevel inference. It turns out that the round holes need round pegs, and that the round pegs are now practicable and easily available in free online statistical software.

Patrick Onghena (Belgium)

Patrick Onghena is professor of educational and behavioral statistics and methodology at KU Leuven, University of Leuven, Belgium. His research interests include single-case experimental designs, distribution-free statistical inference, meta-analysis, systematic reviews, mixed methods research, and research on statistics education and probabilistic reasoning.

Read more

Organized by

Katholieke Universiteit Leuven


Karolinska Institutet

Stockholm, Sweden