Like milk on the stove: Healthcare professionals navigating uncertainty when caring for families with 22q11DS
Bibliographic record
Abstract
INTRODUCTION: 22q11 deletion syndrome (22q11DS) results from a microdeletion on chromosome 22 and is the most common microdeletion disorder in humans, affecting 1 in 2148 live births. Clinical manifestations vary widely among individuals and across different life stages. Effective management requires the involvement of a specialized multidisciplinary team. This study aims to explore the experiences of healthcare professionals in caring for the families of children with 22q11DS, focusing on their challenges, rewards, and coping strategies. METHODS: Data for this interview study were collected as part of a broader mixed methods research project aimed at enhancing the psychosocial well-being of children aged 3-15 years with 22q11DS and their families. The qualitative aspect of this study focused on capturing the experiences of healthcare professionals involved in their care, recruited purposively through collaborators and snowball sampling methods. Reflexive thematic analysis of semi-structured interviews was performed after verbatim transcription. RESULTS: Twenty healthcare providers from different specialties were interviewed. The majority had a working experience of more than 10 years and were part of a 22q11DS clinic. After data analysis, four themes (and many sub-themes) were identified that were all related to the topic of uncertainty: acknowledging uncertainty, sharing uncertainty, acting on uncertainty and coping with uncertainty. Many experts showed a sense of humbleness when caring for the families and most of the participants emphasized the role of peer support and multidisciplinary teams. CONCLUSION: Our study reveals how healthcare professionals manage the uncertainty associated with 22q11DS, highlighting the importance of peer support and multidisciplinary team collaboration. Providers recognize the limits of their medical expertise and value the perspectives of families living with the condition. Their coping strategies play a critical role in handling uncertainty and suggest a need for further emphasis in the literature on the experiences of healthcare professionals dealing with rare diseases.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| 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".