From smoking cessation to physical activity: Can ontology-based methods for automated evidence synthesis generalise across behaviour change domains?

The Human Behaviour-Change Project (HBCP) wants to make it easier to gather and analyse information about how to change people's behaviour. To achieve this, the project collects reports about behaviour change interventions, code them based on an ontology (that is, a classification scheme to organise and represent information within a specific area), and use that data to train computer programs to automatically extract information from reports and make predictions. The project started with smoking cessation as a proof of concept but plans to expand to other behaviours. This study investigates how well the methods used for coding smoking cessation intervention reports could be applied to a new behaviour, physical activity, and describes how this new set of data on physical activity intervention reports was created. Building the HBCP physical activity data set involved: (1) checking if the ontology codes used for smoking cessation would work for physical activity, (2) deciding what kind of physical activity reports to include, (3) finding the reports, and (4) coding the reports using the ontology. During step 1 researchers found that some changes were needed to the codes used for smoking cessation, so they analysed 100 physical activity intervention reports and got feedback from experts to update the codes. After stages 2-4, they ended up with 111 physical activity reports coded using the ontology of behaviour change interventions. In conclusion, the methods used for coding smoking cessation intervention reports could mostly be applied to reports about physical activity interventions, but changes were needed in relation to the target behaviour (for example, how behaviour is measured or whether researchers want people to start vs stop doing something). The aim of this report is to help others looking to build a data set to improve ways in which information on behaviour change interventions is gathered and analysed.

Publication Details

Journal
UCL Discovery (University College London)
Published
2025-03-24
Primary Topic
Water Quality and Resources Studies
Type
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article

From smoking cessation to physical activity: Can ontology-based methods for automated evidence synthesis generalise across behaviour change domains?

UCL Discovery (University College London)
Water Quality and Resources Studies
article

From smoking cessation to physical activity: Can ontology-based methods for automated evidence synthesis generalise across behaviour change domains?

article en

Abstract

The Human Behaviour-Change Project (HBCP) wants to make it easier to gather and analyse information about how to change people's behaviour. To achieve this, the project collects reports about behaviour change interventions, code them based on an ontology (that is, a classification scheme to organise and represent information within a specific area), and use that data to train computer programs to automatically extract information from reports and make predictions. The project started with smoking cessation as a proof of concept but plans to expand to other behaviours. This study investigates how well the methods used for coding smoking cessation intervention reports could be applied to a new behaviour, physical activity, and describes how this new set of data on physical activity intervention reports was created. Building the HBCP physical activity data set involved: (1) checking if the ontology codes used for smoking cessation would work for physical activity, (2) deciding what kind of physical activity reports to include, (3) finding the reports, and (4) coding the reports using the ontology. During step 1 researchers found that some changes were needed to the codes used for smoking cessation, so they analysed 100 physical activity intervention reports and got feedback from experts to update the codes. After stages 2-4, they ended up with 111 physical activity reports coded using the ontology of behaviour change interventions. In conclusion, the methods used for coding smoking cessation intervention reports could mostly be applied to reports about physical activity interventions, but changes were needed in relation to the target behaviour (for example, how behaviour is measured or whether researchers want people to start vs stop doing something). The aim of this report is to help others looking to build a data set to improve ways in which information on behaviour change interventions is gathered and analysed.

UCL Discovery (University College London)
Good health and well-being
Openalex Percentile: Top 56%
Water Quality and Resources Studies
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From smoking cessation to physical activity: Can ontology-based methods for automated evidence synthesis generalise across behaviour change domains? · UCL Discovery (University College London) (2025) | TGRS Research Map | TGRS