Global Workforce Development in Father Engagement Competencies for Family-Based Interventions Using an Online Training Program: A Mixed-Method Feasibility Study
Bibliographic record
Abstract
Global access to practitioner training in the clinical engagement of fathers in family-based interventions is limited. The current study evaluated the feasibility of training practitioners in Canada and UK using online training developed in Australia by examining improvements in practitioner confidence and competence in father engagement, training satisfaction, qualitative feedback, and benchmarking results to those from an Australian sample. Practitioners were recruited to participate in a 2-h online training program through health services and charity organisations. The online program required practitioners to watch a video and complete self-reflection exercises in a digital workbook. Pre- and post-training measures were collected immediately before and after the online training program. The results indicated significantly large improvements in self-reported confidence and competence in engaging fathers following training, with levels of improvement similar to those found in Australia. Training satisfaction was high and qualitative feedback suggested providing local resources and increasing representation of social diversity could improve training relevance in local contexts. The findings suggest online training in father engagement can contribute to global workforce development in improving practitioners' skills in engaging fathers in family-based interventions.
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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 | 0.020 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".