Public Health Nurses’ Professional Practices to Prevent, Recognize, and Respond to Suspected Child Maltreatment in Home Visiting: An Interpretive Descriptive Study
Bibliographic record
Abstract
The purpose of this analysis was to understand public health nurses' experiences in preventing and addressing suspected child maltreatment within the context of home visiting. The principles of interpretive description guided study decisions and data were generated from interviews with 47 public health nurses. Data were analyzed using reflexive thematic analysis. The findings highlighted that public health nurses have an important role in the primary prevention of child maltreatment. These nurses described a six-step process for managing their duty to report suspected child maltreatment within the context of nurse-client relationships. When indicators of suspected child maltreatment were present, examination of experiential practice revealed that nurses developed reporting processes that maximized child safety, highlighted maternal strengths, and created opportunities to maintain the nurse-client relationship. Even with child protection involvement, public health nurses have a central role in continuing to work with families to develop safe and competent parenting skills.
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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 | 0.023 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".