New Approaches to Understand the Intention–Behavior Gap: Testing the Validity of Domain-General but Person-Specific Models
Year: 2026
Type: dissertation
Abstract: The pursuit of well-being and human flourishing depends critically on the successful translationof intentions into action, yet decades of research demonstrate a substantial intention–behavior gap (IBG). Although prior work has often linked goal accomplishment to broad traits such as self-control or conscientiousness, or pursued domain-specific interventions (e.g., voting, exercise, sustainability), such approaches either lack scalability or fail to address person-specific mechanisms. In this dissertation, I advance a domain-general but idiographic account of the IBG, proposing that while the gap reflects a shared mechanism across goal domains, it also exhibits strong heterogeneity across individuals and fluctuates dynamically over time. To evaluate this framework, I first develop and validate a domain-general measure of the intention–behavior gap (DG-IBG). I show that the measure demonstrates significant predictive power for out of sample goal domains for an individual, along with strong associations with well-being. It is also both correlated with and distinct from conventional predictors such as grit or conscientiousness. I then report findings from a 12-week intensive longitudinal design combining pre/post assessments with daily digital trace, survey, and cognitive task data. Analyses reveal systematic violations of ergodicity in the DG-IBG, highlighting non-equivalence between inter- and intra-individual processes and underscoring the need for idiographic modeling. Clustering analyses further suggest meaningful individual differences and equifinality: individuals with comparably sized gaps can arrive there through distinct constellations of internal processes. Finally, I demonstrate that passive digital trace features contain meaningful signal for estimating daily DG-IBG magnitude, with preliminary evidence that idiographic models can outperform group-level models under certain conditions. Together, these findings establish the IBG as a domain-general but idiographic phenomenon, identify it as a promising lever for interventions to enhance well- being, and illustrate the feasibility of personalized, timed, and data-driven strategies to reduce the intention–behavior gap and improve human flourishing.
Source: TSpace (University of Toronto)
Author: Wilson, Daniel J
Institution: University of Toronto
Language: English
Subfield: Applied Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7148192756