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Use of dynamic systems methods to characterize dyadic interactions in smoking cessation behavioural support sessions: A feasibility study

Gainforth, HL; Lorencatto, F; Erickson, K; Baxter, K; Owens, K; Michie, S; West, R; (2019) Use of dynamic systems methods to characterize dyadic interactions in smoking cessation behavioural support sessions: A feasibility study. British Journal of Health Psychology , 24 (1) pp. 192-214. 10.1111/bjhp.12347. Green open access

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Abstract

BACKGROUND: Understanding how behaviour change techniques (BCTs) operate in practice requires a method for characterizing the reciprocal, dynamic, and real-time nature of behavioural support interactions between practitioners and clients. State space grids (SSGs) are an observational, dynamic systems methodology used to map the trajectory of dyadic interactions in real time. By mapping the flow of events in terms of practitioner and client actions, SSGs are potentially well suited to characterize behavioural support sessions. PURPOSE: To develop reliable methods and examine the feasibility of using the SSG methodology for characterizing practitioners' delivery of and clients' response to BCTs in smoking cessation behavioural support sessions. METHODS: Smoking cessation behavioural support sessions were video-recorded and transcribed verbatim (n = 6 recordings; 2,916 statements). All speech was coded independently by two researchers for content and duration using published frameworks for specifying practitioner-delivered and client-received BCTs in smoking cessation interactions. Inter-rater reliability was assessed. Indices of practitioner-client interaction dynamics were derived: (1) reciprocity (i.e., attractor states, content congruence, conditional pairing) and (2) temporal patterning (i.e., variability, inter-grid distance, combinatory micro-patterning, sessional macropatterning). The extent to which indices can describe differences between sessions involving different practitioners and clients was examined. RESULTS: Inter-rater reliability was moderate at 72% agreement. Indices of reciprocity and temporal patterning characterized differences between sessions involving different practitioners and clients. CONCLUSIONS: State space grids provide a method for characterizing the complexity and variability of practitioner-delivered and client-received BCTs in behavioural support sessions. This method has potential to add explanatory value to smoking cessation intervention outcomes. Statement of Contribution What is already known on this subject? Frameworks exist for characterizing practitioner-delivered and client-received behaviour change techniques (BCTs). Methods are still needed to investigate which BCTs are effective under what conditions. State space grids (SSGs) are a dynamic systems method that may better characterize behavioural support interactions. What does this study add? First reliable, dynamic systems, SSG coding procedures, methods, and measures to characterize behavioural support. A method for examining reciprocality and temporal patterning of BCT delivery and receipt. Establishes a dynamic systems method that adds explanatory value to the outcomes of interventions.

Type: Article
Title: Use of dynamic systems methods to characterize dyadic interactions in smoking cessation behavioural support sessions: A feasibility study
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1111/bjhp.12347
Publisher version: https://doi.org/10.1111/bjhp.12347
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Behaviour change techniques, client, dynamic systems, practitioner, smoking, state space grid
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Clinical, Edu and Hlth Psychology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Behavioural Science and Health
URI: https://discovery.ucl.ac.uk/id/eprint/10064724
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