A personalised-approach to identifying important determinants of well-being

Author:

Ciarrochi JosephORCID,Sahdra Baljinder K.ORCID,Hayes Steven C.,Hofmann Stefan G.ORCID,Sanford Brandon,Stanton Cory,Yap Keong,Fraser Madeleine,Gates KathleenORCID,Gloster AndrewORCID

Abstract

Background. Identifying the most important psychological drivers of well-being for a particular individual is critical to developing personalised interventions. Methods. We utilised three, intensive daily diary studies (within person measurement occasions N >50) across three data sets (n1=44; n2=37; n3=141) to examine within-person associations between clinically-relevant processes and a variety of outcomes. We utilised a novel idiographic algorithm, ”i-ARIMAX,” to calculate the strength of relationship (beta) between every process and every outcome within individuals. We then submitted all betas to meta-analytic methods. Results. All process-outcome links were highly heterogeneous between individuals. Processes that were associated with positive outcomes for some people were often unrelated to outcomes for others or associated with negative outcomes. Conclusion. i-ARIMAX might be used to guide personalised interventions and to reduce the number of candidate variables for complicated within-person analysis.

Publisher

Center for Open Science

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