Characteristics of Adolescents Affected by Mass Psychogenic Illness Outbreaks in Schools in Nepal: A Case-Control Study
Bibliographic record
Abstract
Mass psychogenic illness is generally construed as a dissociative phenomenon. We sought to test if the correlates of dissociative experiences and behaviours most commonly proposed in the literature (i.e., that explain dissociation in terms of childhood trauma, cognitive and personality traits, current level of distress, or a specific propensity for dissociative experience and behaviours) could predict caseness among students affected by episodes of mass psychogenic illness occurring in schools in Nepal. We assessed 194 cases and 190 controls (N = 384) of ages 11-18 years from 12 public schools in Nepal. Cases and controls were comparable on all demographic variables, except family configuration. In bivariate comparisons, caseness was associated with childhood trauma (especially physical abuse) as well as living in nuclear families, experience of peritraumatic dissociation, a higher dissociative tendency, and higher levels of depressive and posttraumatic stress symptoms. Hypnotizability emerged as the strongest predictor of mass psychogenic illness case status among the cognitive and personality trait variables. However, in multivariable logistic regression, the proposed correlates of dissociation did not make a significant contribution in predicting caseness suggesting that correlates of dissociative experiences and behaviours currently proposed in the literature do not adequately map the phenomenon of mass psychogenic illness. Ad-hoc Classification and Regression Trees analysis showed that if an adolescent is highly hypnotizable and reports higher rates of peritraumatic dissociative experiences then there is 73% probability that the adolescent will be a case in a mass psychogenic illness episode. Studies involving other psychological factors (i.e., secondary gain, suggestibility, absorption, expectancy, modelling and behavioral mimicry), social and cultural factors as well as school- and family-related factors are needed to understand the causes and correlates of mass psychogenic illness phenomena to guide prevention and intervention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".