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Record W2586736558 · doi:10.1186/s12889-017-4100-7

Participatory science and innovation for improved sanitation and hygiene: process and outcome evaluation of project SHINE, a school-based intervention in Rural Tanzania

2017· article· en· W2586736558 on OpenAlexafffund
Erin Hetherington, Matthijs S. Eggers, Joyce Wamoyi, Jennifer Hatfield, Mange Manyama, Susan Kutz, Sheri Bastien

Bibliographic record

VenueBMC Public Health · 2017
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsHealth Sciences CentreUniversity of Calgary
FundersGrand Challenges CanadaGovernment of CanadaUniversity of Calgary
KeywordsSanitationHygieneMedicineFocus groupImproved sanitationOpen defecationEnvironmental healthSocial marketingPublic healthTanzaniaToiletQualitative researchHealth educationSocioeconomicsNursingSociologyBusinessMarketing

Abstract

fetched live from OpenAlex

BACKGROUND: Diarrheal disease is a major cause of mortality and morbidity in low and middle income countries with children being disproportionately affected. Project SHINE (Sanitation & Hygiene INnovation in Education) is a grassroots participatory science education and social entrepreneurship model to engage youth and the wider community in the development of sustainable strategies to improve sanitation and hygiene. METHODS: Based in rural and remote Tanzania, this pilot study engaged pastoralist high-school students and communities in the development and evaluation of culturally and contextually relevant strategies to improve sanitation and hygiene. Using a train-the-trainer approach, key activities included teacher workshops, school-based lessons, extra-curricular activities, community events and a One Health sanitation science fair which showcased projects related to water, sanitation and hygiene in relation to human and animal health. The process and outcome of the study were evaluated through qualitative interviews and focus group discussions with diverse project participants, as well as pre- and post- questionnaires completed by students on knowledge, attitudes and practices concerning sanitation and hygiene. RESULTS: The questionnaire results at baseline and follow-up showed statistically significant improvements on key measures including a decrease in unhygienic behaviors, an increase in the perceived importance of handwashing and intention to use the toilet, and increased communication in the social network about the importance of clean water and improved sanitation and hygiene practices, however there were no significant changes in sanitation related knowledge. Qualitative data highlighted strong leadership emerging from youth and enthusiasm from teachers and students concerning the overall approach in the project, including the use of participatory methods. There was a high degree of community engagement with hundreds of community members participating in school-based events. Sanitation science fair projects addressed a range of pastoralist questions and concerns regarding the relationship between water, sanitation and hygiene. Several projects, such as making soap from local materials, demonstrate potential as a sustainable strategy to improve health and livelihoods in the long-term. CONCLUSIONS: The Project SHINE model shows promise as an innovative capacity building approach and as an engagement and empowerment strategy for youth and communities to develop locally sustainable strategies to improve sanitation and hygiene.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.184
GPT teacher head0.468
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations33
Published2017
Admission routes2
Has abstractyes

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