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Record W2098058792 · doi:10.1177/1524839912465083

Reconciling Preferences and Constraints in Online Peer Support for Youth With Asthma and Allergies

2012· article· en· W2098058792 on OpenAlexaff
Jeffrey R. Masuda, Sharon Anderson, Nicole Letourneau, Vanessa Sloan Morgan, Moira Stewart

Bibliographic record

VenueHealth Promotion Practice · 2012
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversity of CalgaryUniversity of AlbertaUniversity of Manitoba
Fundersnot available
KeywordsIntervention (counseling)Peer supportPsychologySocial supportHealth promotionPromotion (chess)Medical educationMedicineNursingPublic healthSocial psychology

Abstract

fetched live from OpenAlex

In this article, we examine the opportunities and constraints of professionally mediated social networking in health promotion practice. Our analysis is based on the findings of a 12-week participatory study of a peer-led support intervention for youth with asthma and life-threatening allergies. The article begins with an overview of the preferences of youth, their parents, and young adults recruited as peer mentors for online features in the design of a customized support program. We then briefly explain the rationale behind our decision to design and host our intervention using a publicly available website called Ability Online in an effort to balance participants' preferences with important research obligations and safety requirements. Finally, we report on participants' level of satisfaction with the intervention as well as recommendations for health practitioners who wish to use social networking to enhance supports for youth with chronic health conditions.

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)0.010
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.174
GPT teacher head0.465
Teacher spread0.291 · 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 designQualitative
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

Citations9
Published2012
Admission routes1
Has abstractyes

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