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Record W4312113275 · doi:10.2196/42278

Identification of Key Factors for Optimized Health Care Services: Protocol for a Multiphase Study of the Dubai Vaccination Campaign

2022· article· en· W4312113275 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicQ Methodology Applications
Canadian institutionsnot available
Fundersnot available
KeywordsVaccinationMedicineHealth careGovernment (linguistics)Stratified samplingExcellencePublic healthPopulationFamily medicineEnvironmental healthNursingPolitical scienceImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Mass vaccination of the global population against the novel COVID-19 outbreak posed multiple challenges, including effectively administering millions of doses in a short period of time while ensuring public safety and accessibility. The government of Dubai launched a mass campaign in December 2020 to vaccinate all its citizens and residents, targeting the population aged >18 years against COVID-19. The vaccination campaign involved a transformation of multiple commercial spaces into mass vaccination centers across the city of Dubai, the largest of which was the Dubai One Central (DOC) vaccination center. It was operational between January 17, 2021, and 27 January 27, 2022. OBJECTIVE: The multiphase research study aims to empirically explore the opinions of multiple health care stakeholders, elicit the key success factors that can influence the effective delivery of emergency health care services such as a COVID-19 mass vaccination center, and explore how these factors relate to one another. METHODS: To understand more about the operations of the DOC vaccination center, the study follows a multiphase design divided into 2 phases. The study is being conducted by the Institute for Excellence in Health Professions Education at Mohammed Bin Rashid University of Medicine and Health Sciences between December 2021 and January 2023. To elicit the key success factors that contributed to the vaccination campaign administered at DOC, the research team conducted 30 semistructured interviews (SSIs) with a sample of staff and volunteers who worked at the DOC vaccination center. Stratified random sampling was used to select the participants, and the interview cohort included representatives from the management team, team leaders, the administration and registration team, vaccinators, and volunteers. A total of 103 people were invited to take part in the research study, and 30 agreed to participate in the SSIs. To validate the participation of various stakeholders, phase 2 will analytically investigate one's subjectivity through Q-methodology and empirically investigate the opinions obtained from the research participants during phase 1. RESULTS: As of July 2022, 30 SSIs were conducted with the research participants. CONCLUSIONS: The study will provide a comprehensive 2-phase approach to obtaining the key success factors that can influence the delivery of high-quality health care services such as emergency services launched during a global pandemic. The study's findings will be translated into key factors that could support designing future health care services utilizing evidence-based practice. In line with future plans, a study will use data, collected through the DOC vaccination center, to develop a simulation model outlining the process of the customer journey and center workflow. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42278.

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)0.024
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
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 head0.690
GPT teacher head0.710
Teacher spread0.021 · 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