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Record W4376645072 · doi:10.1093/pch/pxac117

Considerations for privacy and confidentiality in adolescent health care service delivery

2023· review· en· W4376645072 on OpenAlexafffund
Holly Agostino, Alène Toulany

Bibliographic record

VenuePaediatrics & Child Health · 2023
Typereview
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsCanadian Paediatric Society
FundersCollege of Family Physicians of Canada
KeywordsConfidentialityHealth careGuardianAutonomyAgency (philosophy)Internet privacyPsychologyMedicineNursingComputer securityComputer sciencePolitical science

Abstract

fetched live from OpenAlex

A hallmark of delivering quality adolescent health care services is the provision of confidential care. Key tenets when providing confidential care for adolescents include time alone with a health care provider, maintaining the privacy of health information, and securing informed consent for services without permission from a parent, guardian, or caregiver. While confidentiality is a basic principle for all health care encounters regardless of age, the unique considerations for capable adolescent patients are not always realized or appreciated. By ensuring appropriate quantity and quality of confidential care for adolescents, clinicians are better equipped to elicit a comprehensive history and physical examination, while empowering the adolescent involved to develop agency, autonomy, trust, and responsibility for their own health care decision-making and management.

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)0.012
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.208
GPT teacher head0.478
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2023
Admission routes2
Has abstractyes

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