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Record W4311763856 · doi:10.1080/02739615.2022.2156513

Camp health care practices and adaptations associated with COVID-19

2022· article· en· W4311763856 on OpenAlexaboutno aff
Barry A. Garst, Alexsandra Dubin, Tracey Gaslin, Beth Schultz, Michael Ambrose, Andrew N. Hashikawa, Ashley Dehudy

Bibliographic record

VenueChildren s Health Care · 2022
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Communicable diseaseMedicineHygieneVaccinationHealth careQuarter (Canadian coin)NursingEnvironmental healthFamily medicineDiseaseMedical emergencyPublic healthInfectious disease (medical specialty)GeographyVirologyPolitical science

Abstract

fetched live from OpenAlex

The COVID-19 pandemic caused significant changes in camp health care implementation. This study evaluated camp providers’ COVID-19 management practices following the summer of 2021 to inform future communicable disease planning. Online questionnaire data were collected from camp leaders and health care providers (n = 321). Reported COVID-19 cases were very low among both campers and staff. Most camps encouraged camper and staff vaccination before camp, with only a quarter requiring staff vaccination. NPIs used most frequently included cohorting, enhanced cleaning procedures, and scheduled hand hygiene. Camps also reduced the number of campers served and relocated dining, camp health care, and other activities outdoors. A positive correlation was found between requiring staff COVID vaccination and no positive COVID-19 cases. These findings offer insight into communicable disease mitigation strategies and organizational planning that can continue to keep camp populations healthy during communicable disease events like COVID-19.

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 categoriesMeta-epidemiology (narrow), Science 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 score0.320
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
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 head0.066
GPT teacher head0.445
Teacher spread0.378 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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