ABSTRACT
Occasionally, problems are solved with a sudden Aha! moment (insight), while the mundane approach to solving problems is analytical (non-insight). At first glance, non-insight appears to depend on the availability and taxation of cognitive resources to execute the step-by-step approach, whereas insight does not, or to a lesser extent. However, this remains debated. To investigate the reliance of both solution types on cognitive resources, we assessed the involvement of the prefrontal cortex using vagally mediated heart rate variability (vmHRV) as an index. Participants (N = 68) solved 70 compound remote associates word puzzles solvable with insight and non-insight. Before, during, and after solving the word puzzles, we measured the vmHRV. Our results showed that resting-state vmHRV (trait) showed a negative association with behavioural performance for both solution types. This might reflect inter-individual differences in inhibitory control. As the solution search requires one to think of remote associations, inhibitory control might hamper rather than aid this process. Furthermore, we observed, for both solution types, a vmHRV increase from resting-state to solution search (state), lingering on in the post-task recovery period. This could mark the increase of prefrontal resources to promote an open-minded stance, essential for divergent thinking, which arguably is crucial for this task. Our findings suggest that, at a general level, both solution types share common aspects. However, a closer analysis of early and late solutions and puzzle difficulty suggested that metacognitive differentiation between insight and non-insight improved with higher trait vmHRV, and that a unique association between trait vmHRV and puzzle difficulty was present for each solution type.
ABSTRACT
Emotion researchers that use experience sampling methods (ESM) study how emotions fluctuate in everyday life. To reach valid conclusions, confirming the reliability of momentary emotion measurements is essential. However, to minimize participant burden, ESM researchers often use single-item measures, preventing a reliability assessment of people's emotion ratings. Furthermore, because emotions constantly change, checking reliability via conventional test-retest procedures is impractical, for it is impossible to separate measurement error from meaningful emotional variability. Here, drawing from classical test theory (CTT), we propose two time-varying test-retest adaptations to evaluate the reliability of single-item (emotion) measures in ESM. Following Method 1, we randomly repeat one emotion item within the same momentary survey and evaluate the discrepancy between test and retest ratings to determine reliability. Following Method 2, we introduce a subsequent, shortly delayed retest survey and extrapolate the size of test-retest discrepancies to the hypothetical instance where no time between assessments would exist. First, in an analytical study, we establish the mathematical relation between observed test-retest discrepancies and measurement error variance for both methods, based on common assumptions in the CTT literature. Second, in two empirical studies, we apply both methods to real-life emotion time series and find that the size of error in people's emotion ratings corresponds with almost a 10th of the scale, comprising around 27% of the total variability in participants' affective responses. Consequently, disregarding measurement error in ESM is problematic, and we encourage researchers to include a test-retest procedure in their future studies when relying on single-item measures. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
