A public health nursing initiative to promote antenatal health.
Bibliographic record
Abstract
At least one in 10 pregnant women experiences depression. Other health risks during pregnancy include family violence, substance abuse, inadequate nutrition, financial challenges, environmental hazards and lack of social support. Public health nurses are in a unique position to enhance perinatal health by assessing for antenatal psychosocial risk factors. During 2005-06 in a suburban/rural community near Edmonton, Alberta, public health nurses initiated a one-year demonstration project with the goal of increasing the number of health and community services accessed by pregnant women as a result of an interactive appointment with a public health nurse. Eight family physicians in WestView Primary Care Network and three midwives from WestView's Shared Care Maternity Program referred local pregnant clients to the public health nursing unit at WestView Health Centre in Stony Plain. Each woman was assessed by a public health nurse for a variety of psychosocial risk factors. Results of the assessment determined the type of additional health services to which the pregnant women were referred. Care providers were unanimous in their support for public health nurses' continuing to provide antenatal assessments to an expanded population of suburban/rural communities in the Capital Health region.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".