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Record W3080383334 · doi:10.1177/1715163520946079

Pediatric pharmacists’ perspectives on essential skills and activities for community pharmacists caring for pediatric patients: A mixed-methods study

2020· article· en· W3080383334 on OpenAlexaffvenue
Jordan Kelly, Tanner Bengry, Marcel Romanick, Jennifer Jupp, Deonne Dersch‐Mills

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2020
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsMedicineSpecialtyFamily medicinePharmaceutical carePharmacistSet (abstract data type)NursingPharmacy

Abstract

fetched live from OpenAlex

BACKGROUND: Provision of care to pediatric patients represents a set of unique challenges for pharmacists. Pharmacists practising in pediatric-specialty areas (acute care or ambulatory) have unique perspectives on approaches to pediatric care that can be shared to support pharmacists less familiar with this group of patients in providing effective, patient-centred care. METHODS: This was a mixed-methods study using data from pharmacist interviews to quantify and qualitatively describe the approaches to care most commonly reported by pediatric-specialty pharmacists when asked to provide advice to pharmacists on providing pharmaceutical care to infants and children. Data were coded in duplicate using an inductive approach, and discrepancies were resolved by consensus. The number of times a theme (or subtheme) was mentioned and the number of pharmacists who mentioned it were used as markers of the relative importance of the content. RESULTS: The themes (and subthemes) that emerged as most important were clinical activities (dose checks, considering indication, using up-to-date height/weight), caregiver counselling (demonstrating measurement, discussing administration), medication safety (using consistent concentrations of liquids), compounded medications (risks of, use of caution), adherence (formulation considerations, palatability), avoiding use of over-the counter products (except analgesics/antipyretics) and use of external supports (colleagues, caregivers, resources). CONCLUSIONS: 2020;153:xx-xx.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.381
Teacher spread0.325 · 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.

Study designOther design
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

Citations2
Published2020
Admission routes2
Has abstractyes

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