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Record W7038018236

A focus on adolescent mental health and well- being in Europe, central Asia and Canada. Health Behaviour in School-aged Children international report from the 2021/2022 survey.

2023· report· en· W7038018236 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Repository and Bibliography (University of Luxembourg) · 2023
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicEthnobotanical and Medicinal Plants Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthAdolescent healthIntervention (counseling)Central asiaPsychological interventionSocial determinants of healthFocus groupHealth policySurvey data collection
DOInot available

Abstract

fetched live from OpenAlex

The Health Behaviour in School-aged Children (HBSC) study is a large school-based survey carried out every four years in collaboration with the WHO Regional Office for Europe. HBSC data are used at national/regional and international levels to gain new insights into adolescent health and well-being, understand the social determinants of health and inform policy and practice to improve young people's lives. The 2021/2022 HBSC survey data are accompanied by a series of volumes that summarize the key findings around specific health topics. This report, Volume 1 in the series, focuses on adolescent mental health and well-being, using the unique HBSC evidence on the mental health of adolescents aged 11, 13 and 15 years across 44 countries and regions in Europe, central Asia and Canada. It describes the status of adolescent mental health and well-being across a range of indicators, the role of gender, age and social inequality, and how adolescent mental health and well-being has changed over time. Findings from the 2021/2022 HBSC survey provide an important evidence benchmark for current research, intervention and policy-planning.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.030
GPT teacher head0.261
Teacher spread0.231 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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