MétaCan
Menu
Back to cohort

Task‐shifting in the delivery of hormonal contraceptive methods: Validation of a questionnaire and preliminary results

2011· article· en· W2150559415 on OpenAlexaffabout
Édith Guilbert, Diane Morin, Alexis C. Guilbert, Hélène Gagnon, Jean Robitaille, Mary Sue Richardson

Bibliographic record

VenueInternational Journal of Nursing Practice · 2011
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsUniversité LavalInstitut National de Santé Publique du Québec
FundersNational Institutes of Health
KeywordsHormonal contraceptionFamily planningMedicineTask (project management)Family medicineClinical PracticeMedical educationNursingPsychologyGynecologyPopulationResearch methodology

Abstract

fetched live from OpenAlex

Guilbert ER, Morin D, Guilbert AC, Gagnon H, Robitaille J, Richardson M. International Journal of Nursing Practice 2011; 17: 315–321 Task‐shifting in the delivery of hormonal contraceptive methods: Validation of a questionnaire and preliminary results In order to palliate the access problem to effective contraceptive methods in Quebec, Canada, as well as to legitimate nurses' practices in family planning, a collaborative agreement was developed that allow nurses, in conjunction with pharmacists, to give hormonal contraceptives to healthy women of reproductive age for a 6 month period. Training in hormonal contraception was offered to targeted nurses before they could begin this practice. A questionnaire, based on Rogers's theory of diffusion of innovations, was elaborated and validated to specifically evaluate this phenomenon. Preliminary results show that the translation of training into practice might be suboptimal. The validated questionnaire can now be used to fully understand the set of factors influencing this new practice.

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)0.058
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.305

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.083
GPT teacher head0.434
Teacher spread0.351 · 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 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

Citations11
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Nursing PracticeSame topicReproductive Health and ContraceptionFrench-language works237,207