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Record W3045428547 · doi:10.1186/s40545-020-00252-0

Mental health issues impacting pharmacists during COVID-19

2020· article· en· W3045428547 on OpenAlex
Ali Elbeddini, Cindy Wen, Yasamin Tayefehchamani, Anthony To

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Pharmaceutical Policy and Practice · 2020
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMental healthPandemicPharmacistHealth carePharmacyMedicineTriageNursingCoronavirus disease 2019 (COVID-19)Family medicineMedical emergencyPsychiatryDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The coronavirus disease 2019 (COVID-19) impact on the mental health of healthcare workers is extremely detrimental. It is imperative that the psychological health of all healthcare workers be protected. However, an often overlooked member of the healthcare frontline is the pharmacist. Pharmacists provide many types of essential services during the pandemic, which often cannot be done from a remote location. Being frontline healthcare workers, pharmacists have experienced an increase in the number of patients seen, the amount of screening and triage being done, the amount of COVID-19 information being delivered, the number of medication shortages, and the amount of workplace harassment taking place. These activities increase the amount of stress, burden, and frustration felt by pharmacists have a negative impact on their mental health and well-being. This article seeks to address the specific implications of COVID-19 on the mental health of pharmacists.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.677
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.308
GPT teacher head0.625
Teacher spread0.317 · 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