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Record W4387259014 · doi:10.1186/s13012-023-01306-y

Community-engaged optimization of COVID-19 rapid evaluation and testing experiences: roll-out implementation optimization trial

2023· article· en· W4387259014 on OpenAlex
Nicole A. Stadnick, Louise C. Laurent, Kelli L. Cain, Marva Seifert, Maria Linda Burola, Linda Salgin, Paul Watson, William Oswald, Fátima Muñoz, Sharon Velasquez, Justin D. Smith, Jingjing Zou, Borsika A. Rabin

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

VenueImplementation Science · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsChild, Adolescent and Family Mental Health
FundersNational Institute on Minority Health and Health DisparitiesNational Center for Advancing Translational SciencesNational Institutes of HealthFoundation for the National Institutes of Health
KeywordsOperationalizationMedicineCommunity healthPublic healthCommunity engagementHealth informaticsHealth administrationTest (biology)Health services researchNursingMedical educationFamily medicinePublic relations

Abstract

fetched live from OpenAlex

BACKGROUND: There continues to be a need for COVID-19 testing that is pragmatic, community-centered, and sustainable. This study will refine and test implementation strategies prioritized by community partners: (1) walk-up no-cost testing, (2) community health worker (promotores)-facilitated testing and preventive care counseling, (3) vending machines that dispense no-cost, self-testing kits. METHODS: A co-designed Theory of Change from an earlier study phase and the Practical, Robust Implementation and Sustainment Model (PRISM) will guide the study design, measures selection, and evaluation. The first aim is to refine and operationalize a multi-component implementation strategy bundle and outcome measures for COVID-19 testing. A Community and Scientific Advisory Board (CSAB) will be established and include community members, clinical providers/staff from the partnering Federally Qualified Health Center (FQHC), public health researchers, policymakers, and a county health department ambassador. Engagement of CSAB members will be assessed through structured ethnography and a survey about the quality and quantity of engagement practices. The second aim is to implement and evaluate the impact of the implementation strategy bundle to optimize COVID-19 testing in communities using a roll-out implementation optimization (ROIO) design. Seven thousand and five hundred community members will be enrolled across four FQHC clinics over 18 months. Participants will be invited to complete an electronic survey about their demographics, health, and COVID-19 testing results and experiences. CSAB members and clinic partners will participate in PRISM fit and determinant assessments prior to each clinic rollout and post-trial. Interviews will be conducted with 60 community participants and 12 providers/staff following a 3-month rollout period at each clinic, inquiring about their experiences with the implementation strategies. Quantitative data will be analyzed using hierarchical multilevel models to determine the impact of implementation strategies. Qualitative data will be analyzed using rapid qualitative approaches to summarize implementation experiences and identify necessary changes prior to subsequent rollouts. A matrix approach will be used to triangulate data from quantitative and qualitative sources based on PRISM domains. DISCUSSION: This is one of the first pragmatic implementation trials to use a ROIO design and aims to co-create a sustainable and equitable COVID-19 testing program. Findings are likely to generalize to other public health prevention efforts. TRIAL REGISTRATION: NCT05894655 March 2, 2023.

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)0.069
metaresearch head score (Gemma)0.033
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0690.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0110.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.873
GPT teacher head0.746
Teacher spread0.126 · 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