The workshops will be held on the 21st of August, 2018.

N-of-1 design: Opportunities, challenges and solutions for undertaking within participant investigations

Felix Naughton, Dominika Kwasnicka

Full-day Workshop

09:30 – 16:30 , Workshop Room 1

Theories of behaviour change and health behaviour change interventions are usually tested in conventional between-participant designs. However, most of these theories and interventions ultimately focus on within-participant change. This mismatch between the idiographic basis of most theories and intervention causal models and the nomothetic approach of the methodologies typically used to evaluate them is fundamentally problematic. Appreciation of this is fueling the growing interest in N-of-1/within-participant methods in health psychology, yet there is currently a shortage of opportunities to learn about within-participant approaches.

Part I: (1) introduce N-of-1 methods to test a) predictors of behavioural outcomes and b) evaluate interventions using experimental N-of-1 designs, including practical examples; (2) highlight behavioural issues most amenable to N-of-1 investigations.
Part II: (1) introduce advanced issues in N-of-1 research and analysis and (2) using our data (or participants own data) run a ‘hands-on’ session for analysing N-of-1 data and discuss key analysis and methodological challenges.

Part I: Morning workshop: (1) introduction and overview of the N-of-1 design (presentation); (2) priorities of N-of-1 research (small group discussions of advantages and disadvantages of N-of-1, how to apply within-participant designs to their research questions and key priorities e.g., application, personalising interventions, limitations of the design; (3) a workshop summary.  Part II: Afternoon workshop: (1) an overview of advanced issues relevant to N-of-1 methods; (2) a ‘hands-on’ session for participants to use their laptops to run through a method of analysing N-of-1 data and to discuss advanced N-of-1 analysis.

Intended participants
Part I: Anyone can join in as it is a basic overview of N-of-1 method.
Part II: We invite researchers with some prior knowledge and experience of N-of-1 research (i.e., key principles) to join the afternoon session. Participants of Part I will be able to follow through and join in the afternoon session.

Overview (Meta-Review) Methods for Synthesizing Health Psychology Literature

Emily Alden Hennessy, Blair Johnson

Full-day Workshop

09:30 – 16:30 , Workshop Room 2

A growing body of primary study and systematic review literature evaluates health behaviour interventions. Overviews (also known as umbrella reviews or meta-reviews) systematically synthesize this vast and often overwhelming literature to improve its utility; yet, there are few practical guidelines for overview authors to use. This workshop will provide participants with practical steps to address the unique challenges that arise when authors familiar with systematic review methods begin an overview. Upon completion of this workshop, participants should be able to: (1) Describe the role(s) of overviews and identify primary reasons for conducting one. (2) Develop search blocks for different databases sensitive to systematic review literature in their topic of interest. (3) Have a working knowledge overview challenges and options available to address them. And (4) describe, choose, and employ the correct standardized tools for assessing risk of bias and the quality of evidence for their own review.

The workshop will have five sections: (1) Introductions and outline. (2) Define synthesis literature and role of overviews. (3) Search process and paper selection. (4) Challenges unique to overviews and methods to address them (e.g., up-to-datedness, overlap, second-order meta-analyses). (5) Risk-of-bias tool options for overviews (especially AMSTAR and ROBIS) and methods for establishing the quality of the evidence (e.g., GRADE). Attendees will be provided with a workshop manual that includes an outline, copies of the PowerPoint slides used, links to other overview resources, sample exemplary overviews, and a key methods annotated reading list.

Description of intended participants
The workshop is designed for academic and policy-oriented researchers who are interested in synthesizing systematic review and/or meta-analytic literature into an overview. Individuals should have a baseline understanding of synthesis literature so that they are aware of the general process/aims of initiating a systematic literature review.

Writing High Impact Papers and Getting Them Past Desk Rejection: A Strategic Approach

James Coyne

Full-day Workshop

09:30 – 16:30 , Workshop Room 3

(1) Familiarize participants with new electronic resources and the creative purposes to which they can be put.
(2) Provide participants in guided practice in crafting interesting, compelling stories and successful papers.
(3) Provide recognition of what needs to be done after submitting a manuscript, respond to reviews, decide whether to appeal rejections, and manage publicity for new papers

Scientific writing has undergone dramatic changes. Many papers are rejected without being sent for peer review. Other papers appear on PubMed within weeks of submission. Simply reporting good science is insufficient to ensure acceptance. Manuscripts, starting with the cover letter must inspire interest and tell a persuasive story, if they are going to make it to review. Lots of internet resources have become freely available, allowing writers to keep updated on the literature, but also identify potential collaborators, and select the best journals and reviewers. Furthermore, if impact of papers is going to be maximized, authors need to be alert to post-submission responsibilities; respond strategically to reviews including a rejection; and use social media for publicity to increase early citations.

Description of Participants
Graduate and PhD students actively involved in writing; postdocs and junior and senior faculty.

A full day of powerpoint presentations and demonstrations, highly interactive sessions between participants and the presenter in crafting storylines for cover letters and responses to reviewers , picking titles and writing abstracts. Personalized feedback will be provide to participants wherever they are in the writing process.

Introduction to Applying Network Meta-Analysis in Health Psychology

Chris Noone, Gerry Molloy

Full-day Workshop

09:30 – 16:30 , Workshop Room 4

Workshop overview
Network meta-analysis has proven to be a useful tool for comparative effectiveness research of medical and pharmacological interventions – it allows researchers to identify not just whether a particular intervention works, but which intervention works best. It has been used relatively less frequently to examine the comparative effectiveness of interventions in health psychology. One key advantage of network meta-analysis relevant to health psychology is its ability to provide estimates of comparisons for which little or no head-to-head data is available.

Through practical exercises and demonstrations, this workshop will introduce how network meta-analysis works, important considerations for its use in health psychology and how to conduct a network meta-analysis using R. It will also guide researchers in how to appropriately plan the systematic review process when conducting a network meta-analysis.


  • understand what network meta-analysis is and how it works
  • conduct network meta-analysis with continuous and dichotomous data, using R
  • understand the assumptions of network meta-analysis and how to check them
  • be aware of the challenges of using network meta-analysis on behavioural trials

Participants will complete a number of practical exercises including:

  • conducting a pairwise meta-analysis
  • conducting an indirect comparison
  • conducting a network meta-analysis
  • interpreting and critically appraising a network meta-analysis

Description of the intended participants
This workshop is for researchers in health psychology who are interested in using network meta-analysis. Participants should have knowledge of traditional pairwise meta-analysis and an understanding of relevant research design e.g. randomised controlled trials.

Ecological momentary assessment (EMA) methods in health psychology: an introductory workshop

Daniel Powell, Gertraud (Turu) Stadler

Half-day Workshop

09:30 – 12:30 , Workshop Room 5

Ecological momentary assessment (EMA), otherwise known as ambulatory assessment or the experience sampling method, is a method of collecting relatively-intensive repeated measures in daily life. This workshop will provide a “how to” session on EMA research methods for those with interest in incorporating the method into their research.


On completion of the workshop, delegates will be able to:

  • Explain the advantages and disadvantages of using EMA methods in health psychology
  • Identify the potential for EMA studies across different domains: behavioural, cognitive, emotions, symptoms, and physiological.
  • Formulate a within-person research question that is relevant to their own areas of interest
  • Design an appropriate EMA study to address a specific research question
  • Recognise the importance of having a theory of change in EMA research

The half-day workshop will be participatory and interactive, and will assume no or little prior knowledge. Participants will debate how EMA is used in Health Psychology, recognising the benefits but also the potential pitfalls to watch out for. Delegates will learn how to formulate and distinguish within-person from between-person research questions. EMA design will be explored in a short mock protocol task in small groups, with theory of change highlighted as a means of informing design choices. Finally, delegates will be introduced to the multilevel datasets that are typically yielded from EMA studies, addressing some fundamental practical questions: What does multilevel even mean? What does a multilevel dataset look like in SPSS? How straightforward is data linkage across devices? How do I determine statistical power? How much of a problem is missing data?

Description of the intended participants
We welcome all researchers with an interest in designing EMA studies and analysing resultant data.

Using the Person-Based Approach to develop successful health behaviour change interventions

Katherine Bradbury, Leanne Morrison

Half-day Workshop

09:30 – 12:30 , Workshop Room 6


  • Provide an overview of the steps involved in using the Person-Based Approach (PBA) throughout intervention development and implementation
  • Demonstrate how to use the PBA alongside theory- and evidence-based approaches.
  • Provide detailed examples of how the PBA has been applied to optimise a variety of health behaviour change interventions
  • Provide opportunity to practice techniques from the PBA, with feedback from the team

The PBA provides a systematic methodology which can be used to optimise behaviour change interventions. This methodology has been shown to be successful in making interventions more engaging and overcome barriers to uptake and adherence. This workshop will equip users with a detailed understanding of how to use the PBA.

The workshop will begin with an overview of how the PBA can be used to plan and develop successful interventions, as well as to optimise interventions for implementation in real life settings.

We will then present detailed examples which showcase how the PBA is used throughout planning, development and implementation, to maximise successful intervention outcomes. Demonstrations will include how the PBA can be used alongside theory- and evidence-based approaches to provide unique but complementary insights. A key challenge of intervention development is limited time. This workshop will therefore also demonstrate a PBA to rapid analysis of feedback from target users, which ensures efficient optimisation of behavioural interventions.  The examples will include interventions which target patients and healthcare practitioners across a variety of health conditions (hypertension, diabetes, cancer, asthma, weight loss).

Delegates will be invited to:

  • Share their experiences of intervention development/evaluation and partake in discussion on the application of the PBA to their own work.
  • Try out several techniques from the PBA, with opportunity for discussion and feedback from the facilitators.

Intended Participants
Participants can be anyone interested in learning more about the PBA.

An Introduction to Conducting a Discrete Choice Experiment in Health Psychology

Michelle Queally, Edel Doherty

Half-day Workshop

13:30 – 16:30 , Workshop Room 5

Discrete choice experiments (DCEs) are used as a tool in health research to elicit participant preferences for a health product/service or intervention. DCEs are also used in the context of health policy formulation. DCEs are a survey based instrument that help provide a better understanding of how individual choices are made regarding healthcare preferences. DCEs provide valuable feedback regarding factors that should be considered for a given programme or intervention development or health policy formulation. This workshop will provide an overview of and practical introduction to DCEs and how it can be used in health psychology and health behaviour change. Participants will be provided with a step by step guide to designing a DCE survey, including attribute generation for the DCE. A broad overview of basic experimental design and analysis of DCE data will be provided.  No knowledge of economics or DCEs is assumed.


  1. Background information about the theoretical basis for the application of DCEs in health research
  2. Step by step guide to the design of DCE surveys
  3. A broad overview of experimental design and analysis of DCE data
  4. Feedback on group discussion

Activities will include group session work to discuss attribute selection, which is part of the process of designing a DCE. Feedback will then be provided on this session.

Intended Participants
This workshop is aimed at those interested in the application of DCEs in health psychology and will focus on the practical and theoretical issues raised when applying the technique. The workshop will include one group work session which will involve attribute selection, with feedback. No knowledge of economics or DCEs is assumed.

Analysing adherence data in Stata: New analysis methods for mHealth and electronic monitoring.

Garrett Greene, Frank Doyle

Half-day Workshop

13:30 – 16:30 , Workshop Room 6

Numerous devices are now available for precise electronic monitoring of adherence (MEMSTM, INCATM, PropellerTM etc.). New analysis methods are needed to take full advantage of the data provided by these devices, as traditional use of averages or proportions loses too much information and precision. This workshop will introduce recently developed algorithms for processing adherence data, which have been shown to give improved predictions of patient outcomes, and to allow for estimation of optimal doses for specific patient cohorts. This workshop will include theoretical background to these methods, as well as implementation in Stata statistical software.

The workshop will provide instruction in the following:

  • Introduction to Stata and state-of-the-art adherence technologies
  • Theory of adherence monitoring: Choosing the correct adherence measure
  • Implementing the novel Time-Above-Threshold method in Stata (Greene et al., submitted)
  • Using adherence data to determine optimal dosage for individual patients or patient groups


  • Brief overview of adherence devices and analysis methods (1 hr)
    • Overview of adherence technologies and data sources
    • Strengths and weaknesses of current adherence metrics
    • Introduction to new methods
  • Introduction to Stata (1 hr) – hands-on practical session
    • Navigating Stata’s interface and help files
    • Getting data into Stata
    • Applying the Stata language: Clean, modify and generate variables
  • Implementation of new adherence methods in Stata (1.5hrs)
    • Recording and processing of electronic adherence data
    • Implementing and optimising adherence calculations using the Time-Above-Threshold method
    • Determining optimal doses from adherence data