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Record W2785840426 · doi:10.12927/cjnl.2018.25386

Starting at the Beginning: The Role of Public Health Nursing in Promoting Infant and Early Childhood Mental Health

2017· article· en· W2785840426 on OpenAlexaffvenueabout
Lenora Marcellus, Sana Shahram

Bibliographic record

VenueNursing leadership · 2017
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsBritish Columbia Centre on Substance UseUniversity of Victoria
Fundersnot available
KeywordsMental healthNursingPublic health nurseIndigenousPublic healthInfant mental healthPublic health nursingHealth promotionPsychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

The promotion, protection and restoration of mental health are foundational to healthy communities. However, most mental health services in Canada, already underfunded in comparison to hospital-based medical-surgical programs, continue to be focused on providing reactive acute care. Mental health problems in later life often have their roots in the prenatal, infancy and early childhood life periods, and considerable evidence has accumulated about the effectiveness of interventions during this period of time. Although public health nurses (PHNs) play a leadership role in Canada in developing and providing programs that promote mental health in the early years, much of this work is largely invisible. This paper describes the concept of infant and early childhood mental health, identifies key national policies, and explores the role of PHNs in supporting mental wellness for infants and families, in keeping with health equity and Indigenous perspectives. Canadian practice exemplars are provided to highlight the value of investing in the promotion of infant and early childhood mental health.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.520
Threshold uncertainty score0.966

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.010
Scholarly communication0.0080.004
Open science0.0010.006
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.215
GPT teacher head0.405
Teacher spread0.190 · 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 designNot applicable
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

Citations8
Published2017
Admission routes3
Has abstractyes

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