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Record W2151246876 · doi:10.1093/jpepsy/jsl039

Psychological Problems in Children with Bedwetting and Combined (day and night) Wetting: A UK Population-Based Study

2006· article· en· W2151246876 on OpenAlexaff
Carol Joinson, Jon Heron, Alan Emond, Richard Butler

Bibliographic record

VenueJournal of Pediatric Psychology · 2006
Typearticle
Languageen
FieldHealth Professions
TopicNeonatal skin health care
Canadian institutionsChild, Adolescent and Family Mental Health
FundersMedical Research CouncilUniversity of BristolWellcome Trust
KeywordsPsychologyPopulationWettingClinical psychologyPediatricsDevelopmental psychologyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the psychological problems associated with bedwetting and combined (day and night) wetting in children aged around 7(1/2) years. METHODS: Participants were a cohort of over 8000 children enrolled in the population-based Avon Longitudinal Study of Parents and Children. Parents completed postal questionnaires assessing common childhood psychological problems, and children were asked about behavior, friendships, bullying, and self-esteem in clinical interviews. The rates of psychological problems were compared in children with bedwetting, combined wetting, and in children with no wetting problems. RESULTS: The study found a higher rate of parent-reported psychological problems in children with bedwetting and combined wetting compared with those with no wetting problems. Children with combined wetting were particularly at risk for externalizing problems. There was little difference with the child-reported measures. CONCLUSIONS: Bedwetting and combined wetting are associated with parent-reported psychological problems and combined wetting confers an increased risk for externalizing problems.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.396
Teacher spread0.367 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations131
Published2006
Admission routes1
Has abstractyes

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