Measurement invariance and latent mean differences of the morbid curiosity scale (MCS) across the United States and China
Bibliographic record
Abstract
In recent years, there has been a growing body of research focusing on morbid curiosity. However, the development of measurement tools has been slow, with only two scales available. Compared to the unidimensional scale of Curiosity About Morbid Events (CAME) proposed by Zuckerman and Little (1986), the recently developed four-factor Morbid Curiosity Scale (MCS) by Scrivner (2021) demonstrates a stable factor structure and good reliability and validity. As the time since the development of this scale is relatively short, its measurement properties have not been widely evaluated. Therefore, this study used exploratory and confirmatory factor analyses to validate the factor structure of the MCS in the Chinese cultural context, and the results supported the four-factor structure of the MCS. Additionally, we established partial scalar invariance of the MCS between Chinese ( N = 663) and American ( N = 330) cultures, and further analyzed cultural differences in morbid curiosity using latent mean comparison. The results revealed that Chinese individuals had a lower motivation for understanding the minds of dangerous people. This study validated the four-factor Morbid Curiosity Scale across different cultures for the first time, promoting the generalizability of the four-factor MCS and suggesting its potential for use in a wide range of cultural backgrounds. These findings contribute to enriching cross-cultural research on morbid curiosity and its associated psychological factors.
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.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".