Investigating public perceptions and knowledge translation priorities to improve water safety for residents with private water supplies: a cross-sectional study in Newfoundland and Labrador
Bibliographic record
Abstract
BACKGROUND: The first objective of this study was to investigate the public perceptions of private water and alternative sources with respect to safety, quality, testing and treatment in Newfoundland and Labrador (NL), Canada. The second objective was to provide public health practitioners with recommendations for improving knowledge translation (KT) efforts in NL, based on assessments of respondents' perceived information needs and preferred KT methods. METHODS: A cross-sectional telephone survey of 618 households with private water supplies was conducted in March-April, 2007. Questions pertained to respondents' perceptions of their tap water, water concerns, alternative water use, well characteristics, and water testing behaviours. RESULTS: Approximately 94% of households were supplied by private wells (50% drilled and 50% dug wells), while 6% obtained water from roadside ponds, rivers or springs (RPRS). While 85% rated their water quality highly, 55% nevertheless had concerns about its overall safety. Approximately 11% of respondents never tested their water, and of the 89% that had, 80% tested at frequencies below provincial recommendations for bacterial testing. More than one-third of respondents reported treating their water in the home, and 78% employed active carbon filtration methods. Respondents wanted more information on testing options and advice on effective treatment methods. Targeted advertising through television, flyers/brochures and/or radio is recommended as a first step to increase awareness. More active KT methods involving key stakeholders may be most effective in improving testing and treatment behaviour. CONCLUSIONS: The results presented here can assist public health practitioners in tailoring current KT initiatives to influence well owner stewardship behaviour.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".