How We Teach Children with Asthma to Use Their Inhaler: A Scoping Review
Bibliographic record
Abstract
Abstract BackgroundOne reason that asthma remains poorly controlled in children is poor inhaler technique. Guidelines recommend checking inhaler technique at each clinical visit. However, they do not specify how best to train children to mastery of correct inhaler technique. Many children are simply shown how to use inhalers which results in less than 50% with correct inhaler technique. The aim of this scoping review is to explore published literature on teaching methods used to train children to master correct inhaler technique.MethodsWe searched (from inception onwards): Medline, Embase, Scopus, Web of Science, CINAHL and the Cochrane library. We included quantitative studies, (e.g. randomised controlled trials, cohort studies and case-control studies), published from 1956 to present, on teaching inhaler technique to children with asthma. Data was extracted onto a data charting table to create a descriptive summary of the results. Data was then synthesised with descriptive statistics and visual mapping.ResultsTwenty-eight papers were identified for full text analysis. Educational interventions were found to be taking place in a variety of clinical areas and by a range of healthcare professional disciplines. ‘Brief-Instruction’ and ‘Teach-Back’ were identified as two primary methods of providing inhaler technique training in the majority of papers. Secondary themes identified were; use of written instruction, physical demonstration, video demonstrations and/or use of inhaler devices to augment inhaler technique training.ConclusionThere are a variety of means by which inhaler technique has been taught to children. We have not analysed the effectiveness of these different interventions, but have described what has been trialled before in an attempt to focus our attentions on what may potentially work best. The majority of these methods can be dichotomised to either ‘Brief-Intervention’ or ‘Teach-Back’. Based on our analysis of this scoping review, we consider the following as areas for future research; how many times does a given intervention have to be done in order to have the desired effect? For what duration does the intervention need to continue to have a long-lasting effect? And, what is the best outcome measure for inhaler technique? Systematic review registrationOpen Science Framework (osf.io/n7kcw).
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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 | 0.018 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".