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Record W6945243845 · doi:10.25384/sage.c.6883335

Establishing priorities in child health: Giving parents and youth a voice

2023· other· en· W6945243845 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthFocus groupAnxietyCognitionQuality (philosophy)Depression (economics)

Abstract

fetched live from OpenAlex

Parents and youth across Alberta were engaged to identify specific research questions that are a priority to them. Two lists, containing 27 topics were developed with local parent and youth advisory groups, and sent to participants via online questionnaires. Topics were rated from one (least important) to five (most important) and ranked in order of priority. Initial questionnaires were completed by 263 (46%) parents and 308 (54%) youth. Parents rated five topics (behaviour, learning, and developmental disorders; mental health; food, environment and lifestyle; quality of health care; and vaccines) and youth rated four topics (brain and nerve health; mental health; quality of health care; and vaccines) as a high priority. Research questions stemming from 4 parent (12 [5%]) and 6 youth (21 [7%]) focus group discussions were then ranked in a second questionnaire, completed by 43 (43%) parents and 56 (56%) youth. Parents’ highest ranked research question was ‘What is the effect of screen time on cognition and neurodevelopment for children and adolescents?’, while the highest ranked question from youth was ‘What are the early signs of anxiety and depression and when should an individual seek help?’. These topics highlight areas that are important to parents and youth where funding, research, and knowledge mobilization efforts should be directed.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.595
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.163
GPT teacher head0.391
Teacher spread0.227 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2023
Admission routes1
Has abstractyes

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