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Record W3204547233 · doi:10.2196/30757

The COVID-19 Study of Healthcare and Support Personnel (CHAMPS): Protocol for a Longitudinal Observational Study

2021· article· en· W3204547233 on OpenAlexvenueno aff
Peter Kaufmann, Donna Sullivan Havens, Janell L. Mensinger, Patricia K. Bradley, Heather Brom, Linda Carman Copel, Alexander Costello, Christine D’Annunzio, Jennifer Dean Durning, Linda Maldonado, Ann Barrow McKenzie, Suzanne C. Smeltzer, Jennifer Yost

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
FundersVillanova University
KeywordsPsychosocialSnowball samplingHealth careMental healthMedicineLongitudinal studyPandemicWorkforcePopulationObservational studyCohort studyGerontologyPsychological resilienceCohortPsychologyFamily medicineEnvironmental healthCoronavirus disease 2019 (COVID-19)DiseasePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Early in the development of the COVID-19 pandemic, it was evident that health care workers, first responders, and other essential workers would face significant stress and workplace demands related to equipment shortages and rapidly growing infections in the general population. Although the effects of other sources of stress on health have been documented, the effects of these unique conditions of the COVID-19 pandemic on the long-term health and well-being of the health care workforce are not known. OBJECTIVE: The COVID-19 Study of Healthcare and Support Personnel (CHAMPS) was designed to document early and longitudinal effects of the pandemic on the mental and physical health of essential workers engaged in health care. We will investigate mediators and moderators of these effects and evaluate the influence of exposure to stress, including morbidity and mortality, over time. We will also examine the effect of protective factors and resilience on health outcomes. METHODS: The study cohort is a convenience sample recruited nationally through communities, professional organizations, networks, social media, and snowball sampling. Recruitment took place for 13 months to obtain an estimated sample of 2762 adults who provided self-reported information administered on the web through structured questionnaires about their work environment, mental and physical health, and psychosocial factors. Follow-up questionnaires will be administered after 6 months and annually thereafter to ascertain changes in health, well-being, and lifestyle. Participants who consented to be recontacted form the longitudinal cohort and the CHAMPS Registry may be contacted to ascertain their interest in ancillary studies for which they may be eligible. RESULTS: The study was approved by the Institutional Review Board and launched in May 2020, with grants from Travere Therapeutics Inc, McKesson Corporation, anonymous donors, and internal funding from the M. Louise Fitzpatrick College of Nursing at Villanova University. Recruitment ended in June 2021 after enrolling 2762 participants, 1534 of whom agreed to participate in the longitudinal study and the registry as well as to be contacted about eligibility for future studies. CONCLUSIONS: The CHAMPS Study and Registry will enable the acquisition of detailed data on the effects of extended psychosocial and workplace stress on morbidity and mortality and serve as a platform for ancillary studies related to the COVID-19 pandemic. TRIAL REGISTRATION: ClinicalTrials.gov NCT04370821; https://clinicaltrials.gov/ct2/show/NCT04370821. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30757.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.037
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.021
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0030.004
Science and technology studies0.0050.002
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0370.009

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 head0.822
GPT teacher head0.715
Teacher spread0.107 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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

Citations12
Published2021
Admission routes1
Has abstractyes

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