Design thinking to improve rational use of oral rehydration salts: lessons from an innovative co-packaged diarrhoea treatment kit
Bibliographic record
Abstract
Introduction We explored whether greater consideration of product design, informed by end users’ opinions, led to improved utilisation (ie, rational use) of oral rehydration salts (ORS) in home settings. We tested whether a ‘design thinking’ approach, focusing on product acceptability, functionality and ease of use, contributed to an increased likelihood of appropriate ORS use, specifically dosing and preparation of ORS in the correct concentration. Methods Intervention design decisions were used to develop a co-packaged diarrhoea treatment kit containing ORS and zinc, branded as ‘Kit Yamoyo’. In addition to co-packaging, key product design features were the inclusion of 200 mL ORS sachets and a water measurement function incorporated in the packaging design. Cross-sectional data from household surveys of caregivers in rural Zambia were then used to compare ORS preparation and use for diarrhoea patients aged <5 years, who used either the novel co-pack or standard 1 L sachets of ORS. Design benefits were demonstrated to caregivers from two rural areas by trained community health workers (CHWs). Results Odds of correct ORS preparation were 10.93 times greater (p<0.001; 95% CI 5.74 to 20.78) among Kit Yamoyo users versus individuals who used 1 L sachets. Co-pack users prepared ORS to the correct concentration 93% (95% CI 0.89% to 0.96%) of the time, while non-users prepared it in the correct concentration just 60% (95% CI 0.54% to 0.66%) of the time. Conclusion Application of design thinking to the development of a co-packaged ORS and zinc diarrhoea treatment kit, coupled with demonstrations by CHWs, can improve rational use of ORS.
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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 | 0.023 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".