Mothers' decisions about gastrostomy tube insertion in children: factors contributing to uncertainty
Bibliographic record
Abstract
The purpose of this study was to explore O'Connor's four factors contributing to mothers’uncertainty concerning gastrostomy tube (G‐tube) insertion in their children (lack of information; unclear value trade‐offs; lack of support; social pressure) in a substitute decision‐making context. Fifty mothers participated in one semi‐structured interview at the time of their children's G‐tube insertion. Children's ages ranged from 2 weeks to 17 years, slightly more than half were male, and most had a primary diagnosis related to a neurological (n=27) or cardiac (n=10) condition. Two‐thirds of the mothers identified topics about which they wanted more information, the majority reported both gains and losses associated with their decision, three‐quarters reported that they had received support during decision making, and half reported that they had felt pressure from family and health care professionals. Results indicate that mothers’decisions about G‐tube insertion are complex and difficult. The existence and importance of O'Connor's factors in this context are confirmed by mothers’accounts. Because these factors are believed to be modifiable, health care professionals have the opportunity to potentially minimize the extent to which the factors contribute to decision uncertainly. It is recommended that health care professionals implement interventions focused on minimizing uncertainty.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".