Family History Taking in Pediatric Practice: A Qualitative Interview Study
Bibliographic record
Abstract
BACKGROUND: Family history (FH) is a risk factor for many conditions in pediatric practice. There is no standard of care regarding FH taking, and only a few published studies about current practice. OBJECTIVES: To explore in depth pediatricians' perceptions, attitudes, beliefs, and practices regarding FH taking. METHODS: The Theoretical Domains Framework (TDF) was used to develop a comprehensive interview scheme. Semi-structured interviews were conducted with community pediatricians. Interviews were audio-recorded, transcribed, and analyzed using a thematic approach and the constant comparison method. RESULTS: Eleven pediatricians were interviewed. FH was found to be a firmly embedded, complex, and important aspect of pediatric practice. Participants described FH as part of regular holistic care. FH and social history were linked and often appeared to be part of the same concept to participants. FH was used for a range of purposes. In addition to risk assessment, FH information helped clarify diagnosis and select medication, tailor overall patient management based on family circumstance, and provide psychosocial support for parents. Participants expressed confidence in their FH skills and reported tailoring their approach with experience. Most were not concerned about formal evidence for FH and would not change their practice except for "good reason." CONCLUSIONS: The use of the TDF helped ensure a comprehensive approach to FH taking in pediatric practice. The findings suggest that FH taking in this setting is a complex activity, embedded in routine care. Efforts to make FH taking more systematic may founder if they fail to take into account pediatricians' attitudes, perspectives, and practices.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".