Trust of inpatient physicians among parents of children with medical complexity: a qualitative study
Bibliographic record
Abstract
Background: Trust is a foundation of the therapeutic relationship and is associated with important patient outcomes. Building trust between parents of children with medical complexity (CMC) and physicians during inpatient care is complicated by lack of relational continuity, cumulative (sometimes negative) parent experiences and the need to adjust roles and expectations to accommodate parental expertise. This study's objective was to describe how parents of CMC conceptualize trust with physicians within the pediatric inpatient setting and to provide recommendations for building trust in these relationships. Methods: Interviews with 16 parents of CMC were completed and analyzed using interpretive description methodology. Results: The research team identified one overarching meta theme regarding factors that influence trust development: situational awareness is needed to inform personalized care of children and families. There were also six major themes: (1) ensuring that the focus is on the child and family, (2) respecting both parent and physician expertise, (3) collaborating effectively, (4) maintaining a flow of communication, (5) acknowledging the impact of personal attributes, and (6) recognizing issues related to the healthcare system. Discussion: Many elements that facilitated trust development were also components of patient- and family-centered care. Parents in this study approached trust with inpatient physicians as something that needs to be earned and reciprocated. To gain the trust of parents of CMC, inpatient physicians should personalize medical care to address the needs of each child and should explore the perceptions, expertise, and previous experiences of their parents.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".