1194 Targeted Dream Incubation’s Impact on Dream Self-Efficacy & Joy
Bibliographic record
Abstract
Abstract Introduction Targeted Dream Incubation (TDI) is the process of utilizing verbal cues (such as, “while you try to fall asleep, try and think of a tree”) during pre-sleep stages in order to directly shape dream content. Preliminary results have demonstrated that TDI may be able to increase dreaming self-efficacy (DSE). Our study aimed to replicate and extend initial findings by examining TDI’s impact on DSE and related variables. Methods Fifteen participants completed the TDI protocol, which included a pre-nap assessment (baseline), a 1.5-hour nap opportunity, a post-nap assessment, and a one-week follow-up assessment. In all assessments, we measured DSE and subjective feelings related to dreaming. During the nap, when entry into hypnagogia was detected (via a portable EEG system) dream reports were collected and afterwards participants were again given the verbal cue and told to continue sleeping. Non-parametric statistics were used to examine descriptives, compare means, and explore linear relationships. Results Most participants (n = 12; 80%) reported at least one dream that included the cued subject (a tree). Mean comparison analyses found that post-nap DSE (M = 4.56, SD = 1.55) and one-week follow-up DSE (M = 4.45, SD = 1.69; p < 0.05) were both significantly higher than baseline DSE (M = 3.49, SD = 1.54; p < 0.05); and that joy related to dreams measured at the one-week follow-up (M = 4.36, SD = 1.55) was significantly higher than joy related to dreams measured at baseline (M = 3.14, SD = 0.66; p < 0.05). Conclusion Findings both replicate and extend prior research, by demonstrating that TDI may be a reliable method for increasing DSE. Additionally, these findings are the first of their kind to demonstrate that TDI may also impact joy related to dreaming. Both results are quite meaningful as prior research has linked self-efficacy to positive treatment outcomes, and low levels of joy have been linked to outcomes such as depression and suicide. Although statistical power was accounted for, the small sample size is still a limitation of the findings and directly impacts generalizability. Support (if any)
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".