Achieving handwashing with Social Art for Behaviour Change: the experience of the Lazos de Agua programme in Latin America
Bibliographic record
Abstract
The effectiveness of different hygiene behaviour change approaches is inconsistent.Proven effective elements of behaviour promotion include the following: involving the community, adding psychosocial theory-derived elements and using interpersonal communication with active teaching methods and innovative and culturally sensitive messaging.The One Drop Foundation Social Art for Behaviour Change (SABC) approach encompasses those elements and is embedded in a system-strengthening approach involving users, service providers and policymakers within the Lazos de Agua Programme.Halfway into the programme, the SABC approach has been implemented in more than 280 rural and urban communities in five Latin American countries.According to its midline outcome measurement, the programme's efforts have contributed to a 15% point increase in the population practising proper handwashing within intervention areas.Story-based interviews revealed that SABC interventions are believed to have caused lasting changes in behaviour, perception and skills which transcend beyond the individual and are felt at the household and community levels.While the SABC approach is mostly limited to addressing psychosocial factors, the experience of this programme proves that artists can serve as behaviour change facilitators to accompany water, sanitation and hygiene (WASH) system projects.The SABC approach builds capacity, both within artist groups as permanent local institutions which can act as behaviour change facilitation service providers, and within service users, who become empowered and can continue influencing behaviour change among their peers.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| 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".