Exploring family functioning through therapeutic conversations in caregivers of young children undergoing open-heart surgery: A qualitative study
Bibliographic record
Abstract
BACKGROUND: Pediatric open-heart surgery poses significant challenges, as surgical risks and postoperative uncertainties profoundly affect families. Caregivers of young children often face anxiety, exhaustion, and helplessness during intensive care, highlighting the need for developmentally and emotionally responsive support. OBJECTIVES: To explore the impact of therapeutic conversations on the cognitive, emotional, and behavioral domains of family functioning among caregivers of young children undergoing open-heart surgery. DESIGN AND METHODS: This qualitative study employed content analysis to explore caregiver experiences. Semi-structured therapeutic conversations were conducted with 32 caregivers of young children undergoing open-heart surgery at two key time points: before the postoperative day 1 visit and before the child's transfer from the intensive care unit. Conversations were guided by the circular questioning approach of the Calgary Family Intervention Model (CFIM). RESULTS: Analysis of therapeutic conversations identified six themes across cognitive, emotional, and behavioral domains. At previsit, caregivers focused on reducing uncertainty, managing stress, and sustaining coping strategies. By pretransfer, themes shifted to adapting caregiving roles, anticipating future challenges, and reorganizing family life. CONCLUSION: Caregivers' emotional responses shifted from initial anxiety to increased hope and proactive planning, demonstrating the positive impact of CFIM-guided therapeutic conversations. IMPLICATIONS FOR CLINICAL PRACTICE: Nurses should incorporate targeted, relationship-based emotional support strategies, particularly in intensive care settings, to enhance caregiver well-being and strengthen family functioning during the critical postoperative recovery period.
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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 | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".