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Record W2630597126 · doi:10.47339/ephj.2016.101

Environmental health officer’s knowledge of sensory deprivation tanks in BC

2016· article· en· W2630597126 on OpenAlexfundvenueno aff
Alyssa Zambon, Environmental Health BCIT School of Health Sciences, Helen Heacock

Bibliographic record

VenueBCIT Environmental Public Health Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsnot available
FundersBritish Columbia Institute of Technology
KeywordsSanitationTest (biology)Null hypothesisEnvironmental healthPublic healthOfficerPsychologyGeographyBusinessMarketingSocioeconomicsMedicineEngineeringEnvironmental engineeringNursingEcologySociologyBiologyMathematics

Abstract

fetched live from OpenAlex


 Background and Purpose: Personal service establishments are abundant such as piercing shops, tattoo parlours, spas and now float spas. Sensory deprivation tanks were popular in the 1980s and have come back as a new way to relax, reduce pain and relieve stress and to provide a complete deprivation of the senses. The sanitation of these tanks have caused concern in the public health field as bacteria and parasites can easily live and proliferate in the tank water. Environmental Health Officers (EHOs) have to keep up to date with new or returning technology in order to provide information to the public and to ensure their safety. This research project investigated EHOs with differing years of employment in the field, geographic working location and age and their knowledge of sensory deprivation tanks. Methods: A survey created in Google Forms and Survey Monkey was disseminated through e-mail who then forwarded an e-mail to all EHOs in BC. The survey asked demographic questions, health and safety, sanitation and disinfection and general knowledge of floatation tanks. A t-test and ANOVA was used to analyze the data. Results: Three comparisons were tested: first was the number of years an EHO has worked in the field and their test score; second was their age and test score; and last was their geographic location and test score. The null hypotheses were not rejected as the p-value was found to be greater than 0.05 for all of the variables analyzed. Discussion: Overall, there was weak knowledge in EHOs and due to the small sample size there was weak statistical significance between the associations found regarding the number of years an EHO has worked in the field, their age and geographic location where they work compared to their test scores. Conclusion: More information needs to be provided to all EHOs to keep them updated on new personal service establishments.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.302
Teacher spread0.253 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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