Recruitment and retention of fathers with young children in early childhood health intervention research: a systematic review and meta-analysis protocol
Bibliographic record
Abstract
BACKGROUND: Fathers are under-represented in research and programs addressing early childhood health and development. Recruiting fathers into these interventions can be hampered for multiple reasons, including recruitment and retention strategies that are not tailored for fathers. The primary aim of this systematic review and meta-analysis is to determine the effectiveness of recruitment and retention strategies used to include fathers of children (from conception to age 36 months) in intervention studies. The secondary aim is to investigate study-level factors that may influence recruitment and retention. METHODS: We will conduct searches for scholarly peer-reviewed randomized controlled trials, quasi-experimental studies, and pre-post studies that recruited fathers using the following databases: MEDLINE (Ovid), EMBASE (Ovid), PsycINFO (Ovid), and CINAHL. English-language articles will be eligible if they recruited self-identified fathers of children from conception to age 36 months for health-promoting interventions that target healthy parents and children. Two reviewers will independently screen titles/abstracts and full texts for inclusion, as well as grading methodological quality. Recruitment and retention proportions will be calculated for each study. Where possible, we will calculate pooled proportional effects with 95% confidence intervals using random-effects models and conduct a meta-regression to examine the impact of potential modifiers of recruitment and retention. DISCUSSION: Findings from this review will help inform future intervention research with fathers to optimally recruit and retain participants. Identifying key factors should enable health researchers and program managers design and adapt interventions to increase the likelihood of increasing father engagement in early childhood health interventions. Researchers will be able to use this review to inform future research that addresses current evidence gaps for the recruitment and retention of fathers. This review will make recommendations for addressing key target areas to improve recruitment and retention of fathers in early childhood health research, ultimately leading to a body of evidence that captures the full potential of fathers for maximizing the health and wellbeing of their children. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018081332.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.051 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.030 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".