Association between recurrent dreams, disturbing dreams, and suicidal ideation in adolescents.
Bibliographic record
Abstract
Disturbing dreams and recurrent dreams have both been linked to a wide range of\npsychological difficulties in children. There is growing evidence that the experience of\nfrequent disturbing dreams is associated with suicidal ideation in adults but studies in\nyoung adolescents have been limited and the results inconsistent. In addition, the possible\nrelationship between suicidal ideation and recurrent dreams has yet to be studied. We\nthus investigated the relation between disturbing dreams, recurrent dreams and suicidal\nideation in a sample of young adolescents. Self-report measures of disturbing dream\nfrequency, recurrent dream frequency, and suicidal ideation were collected at age 12\nyears and again at age 13 years from 170 children from a prospective population-based\nbirth cohort. While the rate of disturbing dreams and recurrent dreams dropped between\nages 12 and 13, the rate of self-reported suicidal ideation increased between the ages of\n12 and 13 years. Analyses taking sex and age into account revealed that young\nadolescents who reported having had suicidal thoughts over the past year had\nsignificantly greater frequencies of disturbing dreams and of recurrent dreams than\nadolescents who had not thought about suicide. These findings highlight the potential\nclinical value of assessing disturbing and recurrent dreams as part of the screening\nprocess for suicidal ideation in young adolescents.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".