Parents and caregivers experience in managing children’s medicines after discharge from a New Zealand hospital
Bibliographic record
Abstract
AIM: To investigate the level of understanding parents/caregivers have regarding prescribed medicines for their sick children, and how they manage these medicines at home following hospital discharge. METHODS: English-speaking parents/caregivers of sick children were recruited if their child was admitted to Middlemore Hospital in New Zealand and prescribed two liquid medicines, specifically an analgesic and an antibiotic. A questionnaire was developed and used to interview parents/caregivers on three separate occasions. The questionnaire was firstly administered during their hospital stay; secondly, by telephone post-discharge; and thirdly via a home visit two to three days after the estimated completion date of the antibiotic course. RESULTS: Eighteen participants from the five main ethnic groups (Pacific Island n=7, NZ European n=5, Māori n=4, Asian n=2) completed all three interviews. Parents/caregivers had a reasonable understanding of the purpose of the medicines prescribed. Doctors, nurses and pharmacists provided variable medicines information to parents/caregivers on hospital discharge. Parents/caregivers used a variety of measuring equipment at home, but over a quarter (28%) were not supplied with an oral syringe to measure appropriate doses of medicines at home, and some lacked knowledge on safe storage and appropriate disposal of medicines. CONCLUSION: This study found variation and gaps in the information for medicines provided at discharge. To facilitate the safe use of medicines, consistent and clear information about the use, storage and disposal of medicines needs to be provided by all healthcare professionals involved; and accurate measuring equipment should be provided free of charge with instructions.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".