Utilization of the Keeping Hope Possible Toolkit with parents of children with life limiting and life threatening illnesses during the COVID-19 pandemic: Exploring pediatric nurses and allied healthcare provider opinions
Bibliographic record
Abstract
BACKGROUND: For families with children diagnosed with complex illnesses, the COVID-19 pandemic added many challenges. In order to mitigate inevitable disruptions in pediatric care settings, caregivers may need added supports and resources. The Keeping Hope Possible (KHP) Toolkit is a self-administered intervention intended to enhance caregiving experiences of parents with a child with multiple needs. However, little is known about effectively disseminating the Toolkit. PURPOSE AND METHODS: A qualitative, thematic analysis was conducted to explore the opinions and perceptions of pediatric nurses and allied healthcare providers (HCPs) in relation to the dissemination and use of the KHP Toolkit for use by families with complex medical needs. Structured interview data were analyzed from a sample of seven pediatric HCPs working in various care settings in one Canadian province. FINDINGS: Five themes were developed including: Recognising Importance of the KHP Toolkit; Needing Support and Direction; Implementation and Use of the KHP Toolkit; Realizing Important Considerations for Success; and, Emphasizing Connection through Isolated Times. DISCUSSION: Participants recognized the importance of the KHP Toolkit for parents and extended family in a variety of settings to encourage self-care, daily structure, and connectedness. Thus, pediatric nurses' awareness and openness to the initial dissemination of the Toolkit is essential, and a subsequent interprofessional team approach will ensure consistent reminders and support for families. APPLICATION TO PRACTICE: Careful assessment of family readiness for learning about and using the KHP Toolkit is essential, along with an interprofessional approach to consistent inquiry and support at each family encounter.
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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 | 0.011 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| 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".