Community Volunteer Support for Families With Young Children: Protocol for the Volunteer Family Connect Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Use of community volunteers to support vulnerable families is a widely employed strategy with a long history. However, there has been minimal formal scientific investigation into the effectiveness of volunteer home visiting programs for families. There is also a need for research examining whether volunteer home visiting leads to improved outcomes for volunteers. OBJECTIVE: The objective of this paper is to describe the research protocol for a pragmatic randomized controlled trial (RCT) of the Volunteer Family Connect intervention, a volunteer home visiting program designed to support families of young children who experience social isolation or a lack of parenting confidence and skills. The project is being conducted in partnership with 3 leading not-for-profit organizations, designed to contribute to the body of evidence that informs decisions about appropriate family support services according to the level of need. It is the first study to examine outcomes for both the families and the volunteers who deliver the service. METHODS: The RCT is being conducted in 7 sites across Australia. We aim to recruit 300 families to the study: 150 control (services as usual) and 150 intervention (services as usual + volunteer home visiting) families. Intervention families will receive the service for 3-12 months according to their needs, and all participants will complete 6 data collection points over 15 months. A minimum of 80 volunteers will also be recruited, along with a matched community comparison group. The volunteers will complete 3 data collection points over 12 months. Primary outcomes include community connectedness and parenting competence. Secondary outcomes include parent physical and mental health; general parent well-being; parent empowerment; the child-parent relationship; sustainability of family routines; child immunization; child nutrition or breastfeeding; number of accidental injury reports; and volunteer health, well-being, and community connectedness. RESULTS: This effectiveness trial was funded in 2016, and we aim to complete data collection by the end of 2018. The first results are expected to be submitted early in 2019. CONCLUSIONS: There is a need to rigorously assess volunteer home visiting and whether it has a unique and important role on the service landscape, complementary to professional services. This research is the first trial of a volunteer home visiting program to be conducted in Australia and one of the largest of its kind worldwide. TRIAL REGISTRATION: Australian New Zealand Clinical Trial Registry ACTRN12616000396426; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370304 (Archived by WebCite athttp://www.webcitation.org/70q42fU7V). REGISTERED REPORT IDENTIFIER: RR1-10.2196/1000.
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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 | 0.054 | 0.049 |
| Meta-epidemiology (narrow) | 0.009 | 0.005 |
| Meta-epidemiology (broad) | 0.015 | 0.007 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.128 | 0.020 |
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".