Representation of behaviour change interventions and their evaluation: Development of the Upper Level of the Behaviour Change Intervention Ontology

Abstract

Background: Behaviour change interventions (BCI), their contexts and evaluation methods are heterogeneous, making it difficult to synthesise evidence and make recommendations for real-world policy and practice. Ontologies provide a means for addressing this. They represent knowledge formally as entities and relationships using a common language able to cross disciplinary boundaries and topic domains. This paper reports the development of the upper level of the Behaviour Change Intervention Ontology (BCIO), which provides a systematic way to characterise BCIs, their contexts and their evaluations. Methods: Development took place in four steps. (1) Entities and relationships were identified by behavioural and social science experts, based on their knowledge of evidence and theory, and their practical experience of behaviour change interventions and evaluations. (2) The outputs of the first step were critically examined by a wider group of experts, including the study ontology expert and those experienced in annotating relevant literature using the initial ontology entities. The outputs of the second step were tested by (3) feedback from three external international experts in ontologies and (4) application of the prototype upper-level BCIO to annotating published reports; this informed the final development of the upper-level BCIO. Results: The final upper-level BCIO specifies 42 entities, including the BCI scenario, elaborated across 21 entities and 7 relationship types, and the BCI evaluation study comprising 10 entities and 9 relationship types. BCI scenario entities include the behaviour change intervention (content and delivery), outcome behaviour, mechanism of action, and its context, which includes population and setting. These entities have corresponding entities relating to the planning and reporting of interventions and their evaluations. Conclusions: The upper level of the BCIO provides a comprehensive and systematic framework for representing BCIs, their contexts and their evaluations.

Smokers’ Views on Personal Carbon Monoxide Monitors, Associated Apps, and Their Use: An Interview and Think-Aloud Study

“…As per best practice and guidelines for person-centered development of complex digital interventions [ 7 , 8 , 46 ], the study involved a mixed methods approach, involving both in-depth interviews, and think-aloud procedures about a range of prompts, including a modern CO monitoring device, as well as existing and prototype apps. This has enabled a more comprehensive needs assessment among potential end-users of CSSs, as well as exploration of a range of pertinent issues related to the development and evaluation of such programs.…”

“…Research shows that potential users may not be able to articulate all of their preferences, predict their own behavior, or provide justification for these [ 41 , 58 ]. Therefore, future studies should employ other research methods (e.g., observational studies in the wild) to verify the impact of implementing the preferred functionality on engagement and effectiveness of CSSs [ 7 ].…”

“…A potential new cessation aid could involve smartphone-enabled personal testing of carbon monoxide (CO) levels as part of quitting or cutting down. In accordance with principles of user-centered development of complex digital programs [ 7 , 8 ], this study aimed to understand the needs and preferences of potential users to inform further development of and research involving such interventions.…”

“…Furthermore, with the emergence of new technologies and programming solutions, there is also scope for personalization and interaction; integration with other platforms, data sources (e.g., other health indicators) or social media (e.g., buddy systems); and implementation of other interventions (e.g., contingency management programs [ 35 ]). Smartphone apps are also valuable research platforms, enabling efficient data collection and sharing, as well as testing of new design concepts through observational studies, A-B testing, factorial studies, and randomized controlled trials [ 7 ].…”

“…This study aimed to address these gaps. The study is nested within a project that follows guidelines on the development of digital interventions [ 7 ], the Medical Research Council’s Guidance on the development and evaluation of complex interventions [ 46 ] and the Person-Based Approach to intervention development [ 8 , 47 ]. These approaches advocate the process to be iterative and cyclical, involving needs assessment with initial design concepts and research methods consulted among smaller samples of potential end-users, and iteratively adopted before being used in larger or more definitive studies.…”