Testing the dualistic model of passion using a novel quadripartite approach: A look at physical and psychological well‐being
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Passion research has focused extensively on the unique effects of both harmonious passion and obsessive passion (Vallerand, 2015). We adopted a quadripartite approach (Gaudreau & Thompson, 2010) to test whether physical and psychological well-being are distinctly related to subtypes of passion with varying within-person passion combinations: pure harmonious passion, pure obsessive passion, mixed passion, and non-passion. METHOD: In four studies (total N = 3,122), we tested whether passion subtypes were differentially associated with self-reported general health (Study 1; N = 1,218 undergraduates), health symptoms in video gamers (Study 2; N = 269 video game players), global psychological well-being (Study 3; N = 1,192 undergraduates), and academic burnout (Study 4; N = 443 undergraduates) using latent moderated structural equation modeling. RESULTS: Pure harmonious passion was generally associated with more positive levels of physical health and psychological well-being compared to pure obsessive passion, mixed passion, and non-passion. In contrast, outcomes were more negative for pure obsessive passion compared to both mixed passion and non-passion subtypes. CONCLUSIONS: This research underscores the theoretical and empirical usefulness of a quadripartite approach for the study of passion. Overall, the results demonstrate the benefits of having harmonious passion, even when obsessive passion is also high (i.e., mixed passion), and highlight the costs associated with a pure obsessive passion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it