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Record W2009121742 · doi:10.1080/15402000902762360

Imagery Rehearsal Therapy for Frequent Nightmares in Children

2009· article· en· W2009121742 on OpenAlex
Mélanie St-Onge, Pierre Mercier, Joseph De Koninck

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBehavioral Sleep Medicine · 2009
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNightmareDistressPsychologyClinical psychologyGuided imageryPsychiatryAnxiety

Abstract

fetched live from OpenAlex

This study examined the applicability of imagery rehearsal therapy (IRT) to children with frequent nightmares. Eleven boys and 9 girls aged 9 to 11, with moderate to severe primary nightmares (1 or more per week for 6 months) and without posttraumatic stress disorder, were randomly divided into an imagery rehearsal treatment group (n = 9) or a waiting-list (n = 11) group. ANCOVA with repeated measures revealed that, following a baseline period, IRT reduced the frequency of nightmares (p < .04; eta(2) = 0.22) in the treated group compared to the waiting-list group. This reduction was maintained over a 9-month follow-up. The effects of IRT on post-nightmare state distress could not be assessed due to low nightmare incidences. However, retrospective trait nightmare distress was not significantly reduced. Future research is needed to validate this simple approach for nightmare reduction and to evaluate its potential for the reduction of the associated nightmare distress.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.078
GPT teacher head0.382
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it