Personality and wellbeing: Using data mining to refine digital behaviour change interventions

Nathaniel Charlton, John Kingston, Miltiadis Petridis, Ben C. Fletcher

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNpeer-review

Abstract

We study the relationship between personality and wellbeing using questionnaire data from 14,397 people who participated in a digitally delivered Do Something Different (DSD) behaviour change intervention. Our dataset consists of answers to a pre-intervention questionnaire comprising sections addressing behaviour, wellbeing, anxiety and depression, and habits. For 2,863 of these participants, corresponding post-intervention responses are also available. DSD interventions target various health and wellbeing issues such as stress reduction, weight loss, smoking cessation and diabetes self-management. They are based on the psychological theory of behavioural flexibility, developed in a series of books and papers by Fletcher, Pine and others. This paper describes how we applied regression models to data from DSD interventionsto understand better the role of behaviours and personality in wellbeing,and hence refine the theory of behavioural flexibility. We describe our dataset and present a simple model of how behaviours are related to wellbeing; discover that the 30 behaviours listed in the questionnaire can be classified into 9 “inhibitory” and 21 “facilitatory” behaviours; and identify regressions models that predict wellbeing from behaviours more accurately than the existing behavioural flexibility model.
Original languageEnglish
Title of host publicationProceedings of the 2017 International Conference on Digital Health
Place of PublicationNew York
PublisherACM
Pages90-98
Number of pages9
ISBN (Print)9781450352499
DOIs
Publication statusPublished - 5 Jul 2017
EventProceedings of the 2017 International Conference on Digital Health - London, 2-5 July 2017
Duration: 5 Jul 2017 → …

Conference

ConferenceProceedings of the 2017 International Conference on Digital Health
Period5/07/17 → …

Bibliographical note

© 2017 Copyright held by the owner/author(s). This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2017 International Conference on Digital Health, http://dx.doi.org/10.1145/3079452.3079468

Keywords

  • E-health
  • digital health
  • behaviour change
  • nudge
  • statistics
  • classification

Fingerprint

Dive into the research topics of 'Personality and wellbeing: Using data mining to refine digital behaviour change interventions'. Together they form a unique fingerprint.

Cite this