INTERVENTIONS TO ASSIST PARENTS IN ACCURATELY DOSING LIQUID MEDICATIONS FOR THEIR CHILDREN: A SCOPING REVIEW
Bibliographic record
Abstract
Abstract BACKGROUND Parents’ inaccurate dosing of liquid medications for their children is common, resulting in treatment failure and potential adverse effects. Educational interventions delivered by health care professionals are a means to help parents properly administer liquid medications. OBJECTIVES This scoping review was conducted to identify and describe empirically researched educational interventions that prevent inaccurate dosing of liquid medications by parents of children less than 12 years old. DESIGN/METHODS We conducted a scoping review using the Joanna Briggs Institute Methodology for Scoping Reviews. With assistance from a library scientist, we searched PubMed, CINAHL, and Web of Science for English-language articles published before June 2017. We also looked at the reference lists of the included articles and subsequent articles that have cited them to identify additional studies (forward and backward searching). Two reviewers independently screened the retrieved titles and abstracts using predetermined criteria. Only quantitative, empirically designed studies that examined interventions delivered by health care professionals to help parents of children under 12 years old to accurately dose liquid medications were included. We appraised the quality of the included articles using the mixed methods appraisal tool (MMAT) and conducted a thematic analysis to identify trends and patterns. RESULTS Of the 180 abstracts identified in the search strategy, 9 studies met our inclusion criteria. We identified four main types of interventions: 1. use of visual aids (n=6); 2. use of advanced counselling strategies (n=2); 3. use of standardized measuring tools (n=3); and, 4. use of standardized units of measurement (n=2). Some studies evaluated more than one type of intervention. The overall quality of the included studies was moderate, with 11.1% (n=1) scoring 0.25, 33.3% (n=3) scoring 0.50, 55.6% (n=5) scoring 0.75, and none scoring 1.0. CONCLUSION Dosing accuracy of liquid medication for children by their parents is an important topic. More high quality studies conducted by a variety of research groups are needed to ensure the development and implementation of effective evidence-based educational interventions. There is a lack of standardization in the definition of a dosing error. Consensus regarding a standard definition would help studies be more comparable.
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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 | 0.022 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".