A Cross-Sectional Study
Abstract
This proposed study examines how the Dunning–Kruger Effect (DKE), time perspective, life satisfaction, and gambling-related cognitions interact to shape gambling vulnerability, with the goal of identifying cognitive predictors that may inform future intervention strategies. Grounded in metacognitive theory, which conceptualizes biases such as overconfidence as failures in self-assessment and cognitive monitoring, the project highlights how individuals who overestimate their competence may also misjudge their gambling skills or control over outcomes. The proposal argues that this overconfidence may be exacerbated by present-focused time perspectives, lower future orientation, and reduced life satisfaction, particularly in sociocultural environments where modern gambling apps intensify risk-taking behavior. The study’s five hypotheses outline predicted associations among cognitive biases, temporal orientation, subjective well-being, and maladaptive gambling beliefs, including mediation effects in which life satisfaction links time perspective to gambling cognitions. A review of prior research emphasizes the novelty of the effort: while overconfidence and gambling have been examined separately, no existing studies explicitly operationalize all components of the DKE within gambling contexts.
Existing evidence—from studies on perceived control, betting predictions, conjunction fallacies, and overplacement—supports the rationale for a comprehensive evaluation of overconfidence mechanisms related to gambling behavior. Methodologically, the study employs validated assessments of DKE, time perspective, life satisfaction, and gambling cognitions, using multiple regression to test hypothesized relationships in a cross-sectional design. The proposal anticipates outcomes consistent with its theoretical model and describes a realistic timeline, a detailed budget, and plans for dissemination through publication and conference presentation. Overall, the project aims to advance scholarship by integrating cognitive, temporal, and affective predictors of gambling risk within a unified, replicable framework.
- Author(s)
- L.A. Olivera-Figueroa, K.M. Nolla, I.K. Tulloch
- Affiliation
- The Center for Data Analytics and Sports Gaming Research, Morgan State University
- Year
- Ongoing