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

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.     

The assistant referees’ activity in refereeing elite football: Preoccupations when not judging offside

ObjectiveThe purpose of this research was to study the preoccupations assistant referees had to participate in decision making about duels during football games.DesignResearch adopted a phenomenological framework to investigate the assistant referees’ lived experiences in order to understand their activity when they judged duels in match.MethodThis study investigated six professional football matches. Researchers conducted a participatory observation of the refereeing team before each match. Twelve self-confrontation interviews with each assistant referee of each match were conducted in order to make him/her describing his/her unfolding lived experience during the match.ResultsIn case of players’ duels, the perception of contextual cues enabled the assistants to appraise the occurring of a decision process with the central referee. For the assistants, the occurring of a decision process with the central referee meant his priority to intervene in the adjudication of duels, while the absence of decision process with the central referee meant for the assistants the possibility to intervene. The assistants adjusted their way of judging duels to how the central referee judged the previous ones.ConclusionsThe participation of assistants in decision making about duels depends on their preoccupations concerning the central referee’s priority. The way assistants perceive the central referee’s contextual judgment shapes the way they adjudicate duels. A latent intention to coordinate with the central referee, in relation with their collaborative tasks, is embedded in their preoccupations. Our results are a platform to develop further research about the referees’ collective activity.     

Change process in systemic therapy: A qualitative investigation

This study addresses the process of therapeutic change in individuals who received systemic therapy. This study is an exploratory qualitative study based on the client's perceptions and therapeutic experiences. The sample included 10 clients who had completed their therapy with systemic therapists. The method used for the collection of the data was semi‐structured interviews (Change Interview; Elliott, Slatick, & Urman, 2001). The interviews were analysed using grounded theory analysis. The results showed that both specific and common factors in therapy function in a co‐occurring mode, hence suggesting a synergy effect between common factors and specific techniques or therapist factors in psychotherapy. The core category ‘experience of therapeutic change, within the secure frame of therapy, is a process of deconstructing and reconstructing the house you live in: Yourself’ emerged based on self‐exploration and self‐discovery and is then discussed in a theoretical constructivist framework. Implications for research on the issue of the process of therapeutic change are discussed.     

Invidious Comparisons: Imagining a Psychology of Race and Gender Beyond Differences

Within psychology there is a longstanding debate concerning whether large, fundamental differences between races and genders exist. Much of this research involves comparisons that are invidious (offensively discriminating) and supports a political ideology in which members of different groups are held to be fundamentally different, alien, and therefore destined to different spheres. In this paper, specific factors are identified that make research on group differences more likely to produce distorted and partial findings. In addition, studies are cited whose methodological strategies offer insight into the processes that create and maintain group differences. Such research may illuminate not only the differences between groups, but also the very meaning of group categories. The process of scholarly peer review should become sensitive to the features that make comparisons invidious, so as to incorporate them into the criteria used to evaluate research.     

Pairwise comparisons of trimmed means for two or more groups

The paper takes up the problem of performing all pairwise comparisons amongJ independent groups based on 20% trimmed means. Currently, a method that stands out is the percentile-t bootstrap method where the bootstrap is used to estimate the quantiles of a Studentized maximum modulus distribution when all pairs of population trimmed means are equal. However, a concern is that in simulations, the actual probability of one or more Type I errors can drop well below the nominal level when sample sizes are small. A practical issue is whether a method can be found that corrects this problem while maintaining the positive features of the percentile-t bootstrap. Three new methods are considered here, one of which achieves the desired goal. Another method, which takes advantage of theoretical results by Singh (1998), performs almost as well but is not recommended when the smallest sample size drops below 15. In some situations, however, it gives substantially shorter confidence intervals.     

Understanding Dignity in the Lives of Homeless Persons

The current investigation is a planned, systematic study of dignity as critical to understanding the experience of homelessness and improving services and programs for the homeless. Specifically, we conducted a thematic content analysis of interviews with 24 homeless men and women to identify their perception of specific environmental events that validate and invalidate dignity. In addition, we explored the impact that these events have on homeless persons. Eight types of events were identified that sustain dignity such as being cared for by staff and having resources available to meet basic needs. Eight types of events were found that undermine dignity, such as being yelled at or insulted by staff persons and having staff use rules in an excessive and arbitrary way. Two outcomes followed the sustenance of dignity including increased self-worth and motivation to exit homelessness. Three outcomes followed the undermining of dignity including anger, depression, and feelings of worthlessness. The results suggest that dignity is an important variable to consider in understanding the experience of homelessness. Policies and programs that support validating the dignity of homeless persons are encouraged.     

Explanation and the Hard Problem

This paper argues that the form of explanation at issue in the hard problem of consciousness is scientifically irrelevant, despite appearances to the contrary. In particular, it is argued that the ‘sense of understanding’ that plays a critical role in the form of explanation implicated in the hard problem provides neither a necessary nor a sufficient condition on satisfactory scientific explanation. Considerations of the actual tools and methods available to scientists are used to make the case against it being a necessary condition, and work by J.D. Trout that exploits psychological research on the hindsight and overconfidence biases is used to show that it is not a sufficient condition. It is argued, however, that certain intellectual and moral concerns give us good reason to still try to meet the hard problem’s explanatory challenge, despite its extrascientific nature.     

Multilevel Modeling with Correlated Effects

When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized method of moments (GMM) estimation techniques in multilevel modeling, the authors present a series of estimators along a robust to efficient continuum. This continuum depends on the assumptions that the analyst makes regarding the extent of the correlated effects. It is shown that the GMM approach provides an overarching framework that encompasses well-known estimators such as fixed and random effects estimators and also provides more options. These GMM estimators can be expressed as instrumental variable (IV) estimators which enhances their interpretability. Moreover, by exploiting the hierarchical structure of the data, the current technique does not require additional variables unlike traditional IV methods. Further, statistical tests are developed to compare the different estimators. A simulation study examines the finite sample properties of the estimators and tests and confirms the theoretical order of the estimators with respect to their robustness and efficiency. It further shows that not only are regression coefficients biased, but variance components may be severely underestimated in the presence of correlated effects. Empirical standard errors are employed as they are less sensitive to correlated effects when compared to model-based standard errors. An example using student achievement data shows that GMM estimators can be effectively used in a search for the most efficient among unbiased estimators. This research was supported by the National Academy of Education/Spencer Foundation and the National Science Foundation, grant number SES-0436274. We thank the editor, associate editor, and referees for detailed feedback that helped improve the paper.