An ontology-based modelling system (OBMS) for representing behaviour change theories applied to 76 theories

Abstract

Background: To efficiently search, compare, test and integrate behaviour change theories, they need to be specified in a way that is clear, consistent and computable. An ontology-based modelling system (OBMS) has previously been shown to be able to represent five commonly used theories in this way. We aimed to assess whether the OBMS could be applied more widely and to create a database of behaviour change theories, their constructs and propositions. Methods: We labelled the constructs within 71 theories and used the OBMS to represent the relationships between the constructs. Diagrams of each theory were sent to authors or experts for feedback and amendment. The 71 finalised diagrams plus the five previously generated diagrams were used to create a searchable database of 76 theories in the form of construct-relationship-construct triples. We conducted a set of illustrative analyses to characterise theories in the database. Results: All 71 theories could be satisfactorily represented using this system. In total, 35 (49%) were finalised with no or very minor amendment. The remaining 36 (51%) were finalised after changes to the constructs (seven theories), relationships between constructs (15 theories) or both (14 theories) following author/expert feedback. The mean number of constructs per theory was 20 (min. = 6, max. = 72), with the mean number of triples per theory 31 (min. = 7, max. = 89). Fourteen distinct relationship types were used, of which the most commonly used was ‘influences’, followed by ‘part of’. Conclusions: The OBMS can represent a wide array of behavioural theories in a precise, computable format. This system should provide a basis for better integration and synthesis of theories than has hitherto been possible.

Potential Explanations for the Limited Empirical Evidence in Support of Theory in Health Promotion

“…A notable example is the addition of perceived behavioral control to the Theory of Reasoned Action (Ajzen, 2011). Another example is the Health Belief Model (HBM), which is included in the list of theories found in a recently developed ontology-based modeling system designed to assist in the identification, description, and comparison of theories relevant to health behaviors (Hale et al, 2020). The supplementation of a self-efficacy construct to the original formulation of the HBM was in recognition of the importance of this construct as an important determinant of health behavior (Rosenstock, Strecher, & Becker, 1988;Norman & Brain, 2005).…”

Why and how to engage expert stakeholders in ontology development: insights from social and behavioural sciences

“…This ontology aims to represent all features within any behaviour change intervention evaluation report and is being used to guide data synthesis in an Artificial Intelligence system of published behaviour change intervention reports [24]. Associated with this project is a research program, aiming to better specify the plethora of behaviour change theories across disciplines, via graphical, computer-readable representations and formal specifications of terms and relationships [26,27]. However amongst these early advances, ontology development in the social sciences is still relatively novel.…”

The Regression Trap: Why Regression Analyses Are Not Suitable for Selecting Determinants to Target in Behavior Change Interventions

“…This is in line with the crud factor, which refers to "the epistemological concept that, in correlational research, all variables are connected through causal structures which result in real non-zero correlations between all variables in any given dataset" (Orben & Lakens, 2020, p. 241). In fact, correlations between determinants are part and parcel of theories on behavior as indicated by an ontology-based modeling system applied to 76 theories (Hale et al, 2020). This is also key to the mathematical proof of why using regression weights is problematic in determinant selection.…”