Proof‐of‐Concept Evaluation of <scp>EASE</scp> © Family‐Focused Education With Undergraduate Nursing Students
Bibliographic record
Abstract
Nearly a quarter of children worldwide have a parent with mental illness, with impacts on the entire family. Healthcare practitioners can help address the needs of these children and families through family-focused practice. The aim for this proof-of-concept evaluation was to assess the effectiveness and feasibility of a newly developed learning module on the family-focused EASE© (Engage, Assess, Support, Educate) framework, in an undergraduate nursing program. Changes in students' knowledge and confidence in family-focused practice were assessed as well as their overall views of the learning module. A pre/post-online survey was administered to students immediately prior to and 1 week following module delivery. Pre-surveys were completed by 805 students, with 556 (69%) completing post-surveys. Students reported significantly greater knowledge and confidence in working with families and using EASE©. Those who read the pre-reading and had prior experience of working in a mental health service had significantly greater levels of knowledge and confidence. Students with prior experience of working in family services also reported significantly more knowledge. In respect to feasibility, most students (85%) were satisfied with the module. In open-ended responses (n = 168), students described the EASE© framework as easy to understand and important to building confidence in family-focused practice. They acknowledged their limited understandings of child and family needs where parents have mental illness and made recommendations for further development of the module. The findings indicate potential for wider implementation of the EASE© family-focused module across undergraduate healthcare disciplines and development of attendant learning resources for healthcare practitioners.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".