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Record W2593153064 · doi:10.1177/1178630217690193

Self-reported Effects of Water on Health in First Nations Communities in Saskatchewan, Canada: Results From Community-Based Participatory Research

2017· article· en· W2593153064 on OpenAlexaffabout
Cheryl Waldner, Hubert Tote Alimezelli, Lianne McLeod, Rebecca Zagozewski, Lori Bradford, Lalita Bharadwaj

Bibliographic record

VenueEnvironmental Health Insights · 2017
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
Fundersnot available
KeywordsTap waterRespondentWater qualityEnvironmental healthBottled waterCommunity healthOdds ratioCommunity-based participatory researchConfidence intervalMedicinePublic healthGerontologyParticipatory action researchEconomic growthNursingEnvironmental scienceEnvironmental engineeringPolitical scienceEcology

Abstract

fetched live from OpenAlex

Water-related health challenges on First Nations reserves in Canada have been previously documented. Our objective was to describe factors associated with self-reported health effects from tap water in 8 First Nations reserve communities in Saskatchewan, Canada. Community-based participatory approaches were used in designing and implementing cross-sectional household surveys. Individual, household, community, and contextual effects were considered in multilevel analysis. Negative health effects from tap water were reported by 28% of households (n = 579). Concerns about environmental factors affecting water quality (odds ratio [OR] = 3.4, 95% confidence interval [CI] = 1.8-6.7), rarely or never drinking tap water (OR = 2.9, 95% CI = 1.3-6.6), insufficient tap water (OR = 3.0, 95% CI = 1.4-6.3), paying for bottled water (OR = 3.2, 95% CI = 1.2-8.7), and dissatisfaction with tap water were associated with self-reported health effects (n = 393); however, the effect of dissatisfaction was modified by respondent age ( P = .03). Quality and availability were associated with perceptions of health effects from drinking water, providing additional information on how ongoing concerns about drinking water influence self-reported health in some First Nations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.101
GPT teacher head0.349
Teacher spread0.247 · 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 teacher head, not a consensus.

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".

Quick stats

Citations26
Published2017
Admission routes2
Has abstractyes

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