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Record W4379792757 · doi:10.2196/41836

Perceptions of Global Health Engagements in Relation to the COVID-19 Pandemic Among Health Care Workers and Administrators in Western Kenya: Protocol for a Multistage Qualitative Study

2023· article· en· W4379792757 on OpenAlexvenueno aff
Erick Amick, Violet Naanyu, Sherri Bucher, Beverly Henry

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsnot available
FundersNorthern Illinois University
KeywordsQualitative researchHealth careKenyaPublic healthGlobal healthNursingPandemicMedicineReferralEconomic growthPolitical scienceSociologyCoronavirus disease 2019 (COVID-19)Disease

Abstract

fetched live from OpenAlex

BACKGROUND: There has been significant interest in global health in low- and middle-income countries (LMICs) among individuals living in high-income countries (HICs) over the past 30 years. Much of the literature on global health engagements (GHEs) has been presented from the perspective of individuals from high-income countries. Local stakeholders such as health care workers and health care administrators represent critical constituencies for global health activities, yet their perspectives are underrepresented in the literature. The purpose of this study is to examine the experiences of local health care workers and administrators with GHEs in Kenya. We will explore the perceived role GHEs play in preparing the health system to address a public health crisis, as well as their role in pandemic recovery and its aftermath. OBJECTIVE: The aims of this study are to (1) examine how Kenyan health care workers and administrators interpret experiences with GHEs as having advantaged or hindered them and the local health system to provide care during an acute public health crisis and (2) to explore recommendations to reimagine GHEs in a postpandemic Kenya. METHODS: This study will be conducted at a large teaching and referral hospital in western Kenya with a long history of hosting GHEs in support of its tripartite mission of providing care, training, and research. This qualitative study will be conducted in 3 phases. In phase 1, in-depth interviews will be conducted to capture participants' lived experience in relation to their unique understandings of the pandemic, GHEs, and the local health system. In phase 2, group discussions using nominal group techniques will be conducted to determine potential priority areas to reimagine future GHEs. In phase 3, in-depth interviews will be conducted to explore these priority areas in greater detail to explore recommendations for potential strategies, policies, and other actions that might be used to achieve the priorities determined to be of highest importance. RESULTS: The study activities commenced in late summer 2022, with findings to be published in 2023. It is anticipated that the findings from this study will provide insight into the role GHEs play in a local health system in Kenya and provide critical stakeholder and partner input from persons hitherto ignored in the design, implementation, and management of GHEs. CONCLUSIONS: This qualitative study will examine the perspectives of GHEs in relation to the COVID-19 pandemic among Kenyan health care workers and health care administrators in western Kenya using a multistage protocol. Using a combination of in-depth interviews and nominal group techniques, this study aims to shed light on the roles global health activities are perceived to play in preparing health care professionals and the health system to address an acute public health crisis. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/41836.

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)0.043
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.043
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.026
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0090.005
Scholarly communication0.0040.004
Open science0.0040.005
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0310.005

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 head0.467
GPT teacher head0.687
Teacher spread0.220 · 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 designQualitative
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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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