N-of-1 methods: A practical guide to exploring trajectories of behaviour change and designing precision behaviour change interventions

Tools

Kwasnicka, Dominika and Naughton, Felix (2020) N-of-1 methods: A practical guide to exploring trajectories of behaviour change and designing precision behaviour change interventions. Psychology of Sport and Exercise, 47. ISSN 1469-0292

Preview

PDF (Accepted_Manuscript) - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.
Download (1MB) | Preview

Abstract

Objectives: (1) To introduce N-of-1 methods and how they can help the researchers identify predictors of behavioural outcomes, (2) to provide examples of studies that test individual theory-based predictions of physical activity and/or exercise; (3) to provide a practical example dataset to illustrate how to design and undertake a basic analysis for an N-of-1 study; and (4) to suggest a future agenda for N-of-1 physical activity and exercise research. Design: Factors for consideration when designing an N-of-1 study include variability of predictors and outcomes, assessment frequency and appropriate analysis methods. Existing literature and piloting can help inform these aspects. Methods We use a dataset of 24 individuals who collected data over 28 days to illustrate example analysis procedures. Data, guidance and associated SPSS and R syntax are made available to provide researchers with tools to learn about and practice N-of-1 analysis. Results: Guidance on dealing with missing data, looking at graphical representations of N-of-1 data, managing autocorrelation using the prewhitening method and analysing N-of-1 datasets is provided. Using the example dataset, we demonstrate how to identify antecedents of physical activity (steps) to assess directionality of associations. We also include an overview of aggregating N-of-1 datasets using multilevel modelling. Conclusions: N-of-1 methodology provides a means of tracking individual patterns of behaviour and identifying potential antecedents of physical activity and exercise to help determine causality. Assisted by mobile technologies, there is great potential to enrich our understanding of movement behaviour using this approach to inform interventions.

Item Type:	Article
Uncontrolled Keywords:	idiographic methods,n-of-1,n-of-1 analysis,r,spss,statistics,within person design,applied psychology ,/dk/atira/pure/subjectarea/asjc/3200/3202
Faculty \ School:	Faculty of Medicine and Health Sciences > School of Health Sciences
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Groups > Health Promotion Faculty of Medicine and Health Sciences > Research Groups > Behavioural and Implementation Science Faculty of Medicine and Health Sciences > Research Centres > Norwich Institute for Healthy Aging Faculty of Medicine and Health Sciences > Research Centres > Lifespan Health
Related URLs:	http://www.scopus.com/inward/record.url?... https://linkinghub.elsevier.com/retrieve...
Depositing User:	LivePure Connector
Date Deposited:	08 Aug 2019 08:30
Last Modified:	29 Jan 2025 12:34
URI:	https://ueaeprints.uea.ac.uk/id/eprint/71917
DOI:

Downloads

Downloads per month over past year

Actions (login required)

View Item