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Record W2561482167 · doi:10.1007/s00787-016-0935-1

Identifying disordered eating behaviours in adolescents: how do parent and adolescent reports differ by sex and age?

2017· article· en· W2561482167 on OpenAlexaff
Savani Bartholdy, Karina Allen, John Hodsoll, Owen O’Daly, Iain C. Campbell, Tobias Banaschewski, Arun L.W. Bokde, Uli Bromberg, Christian Büchel, Erin Burke Quinlan, Patricia Conrod, Sylvane Desrivières, Herta Flor, Vincent Frouin, Jürgen Gallinat, Hugh Garavan, Andreas Heinz, Bernd Ittermann, Jean‐Luc Martinot, Éric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Michael N. Smolka, Eva Mennigen, Henrik Walter, Robert Whelan, Günter Schumann, Ulrike Schmidt

Bibliographic record

VenueEuropean Child & Adolescent Psychiatry · 2017
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of TorontoBaycrest HospitalUniversité de Montréal
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute of Mental HealthMedical Research CouncilNational Institutes of HealthTHIS Institute, University of CambridgeInnovative Medicines InitiativeSixth Framework ProgrammeForskningsrådet om Hälsa, Arbetsliv och VälfärdFondation pour la Recherche MédicaleNational Institute for Health and Care ResearchAssistance Publique - Hôpitaux de ParisBundesministerium für Bildung und ForschungFondation de FranceSeventh Framework ProgrammeSvenska Forskningsrådet FormasWellcome TrustAgence Nationale de la RechercheDeutsche ForschungsgemeinschaftEuropean CommissionUniversity of Cambridge
KeywordsDisordered eatingBinge eatingOddsEating disordersChild and adolescent psychiatryPsychologyDistressEpidemiologyDemographyOdds ratioYoung adultClinical psychologyMedicinePsychiatryDevelopmental psychologyLogistic regression

Abstract

fetched live from OpenAlex

This study investigated the prevalence of disordered eating cognitions and behaviours across mid-adolescence in a large European sample, and explored the extent to which prevalence ratings were affected by informant (parent/adolescent), or the sex or age of the adolescent. The Development and Well-Being Assessment was completed by parent-adolescent dyads at age 14 (n = 2225) and again at age 16 (n = 1607) to explore the prevalence of 7 eating disorder symptoms (binge eating, purging, fear of weight gain, distress over shape/weight, avoidance of fattening foods, food restriction, and exercise for weight loss). Informant agreement was assessed using kappa coefficients. Generalised estimating equations were performed to explore the impact of age, sex and informant on symptom prevalence. Slight to fair agreement was observed between parent and adolescent reports (kappa estimates between 0.045 and 0.318); however, this was largely driven by agreement on the absence of behaviours. Disordered eating behaviours were more consistently endorsed amongst girls compared to boys (odds ratios: 2.96-5.90) and by adolescents compared to their parents (odds ratios: 2.71-9.05). Our data are consistent with previous findings in epidemiological studies. The findings suggest that sex-related differences in the prevalence of disordered eating behaviour are established by mid-adolescence. The greater prevalence rates obtained from adolescent compared to parent reports may be due to the secretive nature of the behaviours and/or lack of awareness by parents. If adolescent reports are overlooked, the disordered behaviour may have a greater opportunity to become more entrenched.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.288
Teacher spread0.267 · 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

Citations70
Published2017
Admission routes1
Has abstractyes

Explore more

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