Follow-up study of private well users affected by groundwater arsenic in the Surrey-Langley area
Bibliographic record
Abstract
Background: Arsenic is a potent toxicant and Group 1 human carcinogen which occurs naturally in certain sediments and can contaminate groundwater. In the Surrey-Langley area of British Columbia, a 2007 study of private wells found that 43% of wells tested contained arsenic concentrations above the maximum acceptable concentration (MAC) prescribed in Health Canada’s Guidelines for Canadian Drinking Water Quality. The well owners who participated in the 2007 study were informed of the results and of effective treatment methods that would remove the arsenic contamination. This is a follow-up study that surveyed affected well users approximately 10 years later in order to identify whether the well users had subsequently made any water treatment or behavioral changes to improve the quality of their drinking water, and also to determine whether knowledge translation of the arsenic risk had been effective. Methodology: This study contacted and enrolled private well users who were living at properties which had previously been included in the 2007 study and, in 2007, were found to have arsenic levels above the MAC in the groundwater. Respondents who agreed to participate completed a questionnaire designed to identify what treatment methods or behavioral methods they use to mitigate the risk posed by arsenic contamination. Pre-treatment and post-treatment samples of their drinking water were collected and the arsenic concentrations were analyzed. The effectiveness of treatment devices for arsenic removal was evaluated. The groundwater arsenic concentrations from approximately 10 years apart were compared to identify if arsenic levels had changed. Results: Of the 42 properties that participated in the 2007 study and had groundwater arsenic levels above the MAC, 17 participated in this follow-up study. 14 of the participants also took part in the 2007 study 10 years ago. 79% of participants had not known prior to taking part in the 2007 study that their drinking water contained arsenic levels above the MAC. All 79% then either installed reverse osmosis treatment devices to remove arsenic from their drinking water, or switched to using bottled water for drinking. This indicates that knowledge translation of the health risk was effective. Of the 8 properties using treatment devices rather than bottled water, to mitigate the arsenic risk, 2/8 (25%) were ineffective at reducing arsenic. In addition, arsenic groundwater concentrations were not found to have changed significantly in 10 years (p = 0.11). Conclusion: Participation in the 2007 study was viewed as useful and informative by participants. Knowledge translation of the health risk and the need for risk mitigation was effective, but 25% of treatment devices were found to be ineffective at removing arsenic from drinking water. These results suggests that further knowledge translation of the need for routine testing for arsenic in post-treated drinking water may be beneficial to affected private well users.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".