An integrative review of family supports as components of early childhood home visiting models
Bibliographic record
Abstract
ABSTRACT Objective We conducted an integrative review to identify family support categories that have been described as components of early childhood home visiting models in empirical research and to distinguish whether supports were formal or informal. Background Key components of most early childhood home visiting models include family supports intended to promote child and family outcomes. Categories of family support have been described in other extant literature: (a) material, (b) informational, (c) social–emotional, and (d) organizational. Family support has been further categorized as formal or informal. In this literature, informal supports have been characterized as more enduring and meaningful than formal ones. Method A systematic literature search was conducted. A total of 244 studies representing 127 early childhood home visiting models were located and coded. Results Formal informational supports were the most frequently reported family support category. Informal supports were reported much less frequently than formal supports. Conclusion Given the enduring impacts of informal family supports, home visiting models should include both informal and formal supports. Empirical studies should include descriptions of the types of family supports in home visiting models and more explicitly hypothesize linkages to intended outcomes. Implications Future work should include refining the definitions of support categories, distinguishing informal and formal supports, exploring interactions among supports, and understanding the functions of supports from the perspectives of families and home visitors.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".