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Record W110444075 · doi:10.1177/070674370004500107

Ethical Issues concerning Participants in Community Surveys of Child and Adolescent Mental Disorders

2000· article· en· W110444075 on OpenAlexaffvenue
Suzanne Lépine, Nicole Smolla

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicSurvey Methodology and Nonresponse
Canadian institutionsHôpital Rivière-des-Prairies
Fundersnot available
KeywordsPsychologyMental healthPsychiatryClinical psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Considering that a literature review yielded limited information on ethical issues concerning participants in child and adolescent mental health community surveys, the authors identify and discuss some of these issues. METHOD: First, the authors present the ethical principles set forth by the National Council on Bioethics in Human Research (NCBHR) and evoked by the 1998 Tri-Council Policy Statement, underscoring their importance as guidelines for establishing ethical standards for research with children. Second, they describe the general objectives and currently preferred methods of child psychiatric surveys. Third, they discuss issues pertaining to the validity and innocuousness of structured interview guides, the limitations of parental authorization and children's assent, and the complexity of clinical interventions based on ethical grounds. CONCLUSIONS: The authors emphasize the importance of developing empirical knowledge regarding the questions raised and bringing the social stakeholders concerned into the debate.

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)0.395
metaresearch head score (Gemma)0.474
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.746

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3950.474
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0070.011
Scholarly communication0.0050.005
Open science0.0030.005
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.155
GPT teacher head0.423
Teacher spread0.268 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
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

Citations9
Published2000
Admission routes2
Has abstractyes

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