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Record W2266365024 · doi:10.5539/jedp.v6n1p104

Do Parental Reports of Routinized and Compulsive-Like Behaviours Decline with Child’s Age?: A Brief Report of a Follow-Up Study

2016· article· en· W2266365024 on OpenAlexvenueno aff
Sheila Glenn, Angela Nananidou

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsWorryPsychologyAnxietyDevelopmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

<p><em>Background</em>: Routinized and compulsive-like behaviours are very common in young children; however, previous studies have shown inconsistent results as to the age such behaviours decline. Another issue concerns any association with later Obsessive-Compulsive Disorder (OCD). <em>Method</em>:<strong> </strong>Related measures longitudinal design:<strong> </strong>We compared parent ratings of children over a 6 year period. The sample consisted of 109 children (aged 8 to 18 years, 62 males). Measures were of routinized and compulsive-like behaviours, OCD behaviours, worries and fears. <em>Results</em>: Routinized behaviours decreased significantly over the 6 year period, but not for children reported to have difficulties. OCD behaviours increased significantly with 31% of the sample having above threshold scores; however, only one child in the sample had an OCD diagnosis. There were significant correlations between CRI, OCD and fear and worry scores.<em> Conclusion</em>:<em> </em>We confirmed the view that anxiety reduction is one of the functions of routinized behaviours. A small number of children had high scores on routinized behaviours and the OCD measure, but there was only 1 diagnosis of OCD in the sample. This suggests that they may be part of the typical distribution of such behaviours.</p>

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.336
Teacher spread0.317 · 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 teacher head, not a consensus.

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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Educational and Developmental PsychologySame topicObsessive-Compulsive Spectrum DisordersFrench-language works237,207