N-of-1 methods: A practical guide to exploring trajectories of behaviour change and designing precision behaviour change interventions |
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| Affiliation: | 1. SWPS University of Social Sciences and Humanities, Aleksandra Ostrowskiego 30b, 53-238, Wrocław and School of Public Health, Curtin University, Kent Street, Perth, 6102, Western Australia, Australia;2. School of Health Sciences, University of East Anglia, Norwich, NR4 7UL, United Kingdom;1. Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No. 199 Donggang West Road, Chengguan District, Lanzhou, 730000, China;2. Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, No. 199 Donggang West Road, Chengguan District, Lanzhou, 730000, China;3. Office for Cancer Screening Program in Urban China, Cancer Hospital, Chinese Academy of Medical Sciences, National Cancer Center of China, No.17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China;4. Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Chaoyang District, Beijing, 100101, China;5. Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada;6. Complementary and Alternative Research and Education (CARE) Program, Department of Pediatrics and School of Public Health, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada;7. Department of Psychiatry, Columbia University, New York, USA;8. Department of Biostatistics, Columbia University, New York, USA;9. Center for Clinical Epidemiology and Biostatistics and Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA;10. Department of Internal Medicine and Center for Healthcare Policy and Research, University of California Davis, 4150 V Street, Suite 2400 PSSB, Sacramento, CA 95817, USA;1. School of Human Kinetics and School of Psychology, University of Ottawa, Ontario, Canada;2. Institut du savoir de l’Hôpital Montfort (ISM), Hôpital Montfort, Ontario, Canada;3. Cancer Therapeutic Program, Ottawa Hospital Research Institute (OHRI), Ontario, Canada;4. Department of Supportive Care, Princess Margaret Cancer Centre, Toronto, Ontario, Canada;5. Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada;6. Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, Ontario, Canada;7. Wellspring Cancer Support Network, Toronto, Ontario, Canada;1. School of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton, Queensland, Australia;2. Appleton Institute, Central Queensland University, Adelaide, South Australia, Australia;3. School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia;4. Black Dog Institute, Prince of Wales Hospital, Sydney, New South Wales, Australia;5. St John of God Health Care, Richmond Hospital, North Richmond, New South Wales, Australia |
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| 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.DesignFactors 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.MethodsWe 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.ResultsGuidance 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.ConclusionsN-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. |
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| Keywords: | N-of-1 Idiographic methods Within person design N-of-1 analysis R SPSS Statistics |
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