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Record W2078035110 · doi:10.1089/apc.2005.19.840

People with HIV as Educators of Health Professionals

2005· article· en· W2078035110 on OpenAlexaff
Patricia Solomon, Dale Guenter, Deborah Stinson

Bibliographic record

VenueAIDS Patient Care and STDs · 2005
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsOntario AIDS NetworkMcMaster University
Fundersnot available
KeywordsMedicineHuman immunodeficiency virus (HIV)Qualitative researchHealth professionalsVariety (cybernetics)NursingMedical educationFamily medicineHealth care

Abstract

fetched live from OpenAlex

This qualitative study examined the impact upon people living with HIV (PHAs), of being trained and utilized as educators of health professionals. PHAs participated in a training program to help them develop skills to facilitate learners in problem-based educational events. After training the PHAs participated in small group problem-based tutorials with separate groups of physiotherapy and occupational therapy students and family medicine residents. Content analyses of the PHAs' reflective journals and semistructured interviews conducted at completion of the project indicated there was a positive impact on their teaching skills, self-awareness, personal understanding of HIV, confidence in teaching, and everyday life. Learner feedback indicated that they valued their interactions with the PHAs. This model of education has the potential to positively benefit patients living with a variety of illnesses and disabilities.

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)0.007
metaresearch head score (Gemma)0.017
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.401
Teacher spread0.388 · 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

Citations45
Published2005
Admission routes1
Has abstractyes

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