MétaCan
Menu
Back to cohort
Record W3167513946 · doi:10.1177/13674935211026123

Child and family health nurses’ roles in the care of infants and children: A scoping review

2021· review· en· W3167513946 on OpenAlexaboutno aff
Louise Wightman, Alison Hutton, Julian Grant

Bibliographic record

VenueJournal of Child Health Care · 2021
Typereview
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipIntervention (counseling)NursingMedicineHealth careHealth promotionChild developmentFamily medicinePublic healthPsychiatryPolitical science

Abstract

fetched live from OpenAlex

Child and family health nurses (CFHNs) work in a variety of settings with families to promote optimal growth and development in infants and children from birth to 5 years. Literature is available about models of care that CFHNs use in their work, but there is limited information about how CFHNs enact care specifically for infants and children. The aim of this scoping review was to identify and contextualize existing knowledge of how CFHNs, both in Australia and internationally, care for infants and children. Arksey and O'Malley's (2005) framework was used to review 27 studies from Australia, Sweden, Finland, United Kingdom (UK), United States of America (USA), Ireland, Netherlands, Denmark and Canada. It was identified that CFHNs, equipped with a range of assessment tools for early intervention and health promotion, use a partnership approach when working with parents to promote the health and well-being of infants and children. The literature revealed the complexity of the roles undertaken by CFHNs when caring for infants and children. Review findings indicated that CFHNs' work is distinctive because it is conducted in home and community settings, is relational and salutogenic in nature and is also located in the domain of preventative health and early intervention.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.006
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.046
GPT teacher head0.468
Teacher spread0.421 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review · Other design
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

Citations29
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Child Health CareSame topicChild and Adolescent HealthFrench-language works237,207