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Record W4225305164 · doi:10.1038/s41598-022-11072-4

Reliability, usability and identified need for home-based cardiometabolic health self-assessment during the COVID-19 pandemic in Soweto, South Africa

2022· article· en· W4225305164 on OpenAlexaff
Clara Calvert, Andrea Kolkenbeck‐Ruh, Simone H. Crouch, Larske M. Soepnel, Lisa J. Ware

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsCentre for Global Health Research
FundersUniversity of EdinburghWellcome Trust
KeywordsPandemicCoronavirus disease 2019 (COVID-19)UsabilityReliability (semiconductor)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Computer scienceMedicineGeographyData scienceVirologyOutbreakInternal medicine

Abstract

fetched live from OpenAlex

A major obstacle to tackling the growing burden of chronic disease in South Africa is lack of testing, particularly where individuals face multiple barriers to accessing health services. We conducted a pilot study to evaluate a cardiometabolic self-measurement kit, including assessment of blood pressure, obesity and urine analysis, amongst adults in Soweto, South Africa. Participants (N = 94) were recruited by researchers during community health screening and were provided with a home test kit including a tablet with self-measurement instructions. The participants entered their results on the tablet and, on completion, the researcher immediately repeated the measurements. We interviewed 10% of participants to understand their experience and views of the kits. Concordance correlation coefficients ranged from 0.78 for waist circumference to 0.93 for height, while the overall percentage agreement ranged from 80.5% for both urine protein and urine glucose testing to 91.4% for the identification of central obesity (ratio of waist circumference to height of ≥ 0.5). Participants saw the need for self-testing and found the process for the most part simple, though urine testing and height self-assessment presented some challenges. This pilot study suggests that self-assessment at home has the potential to facilitate the identification of individuals at risk for cardiometabolic disease in low-income settings, adding to a growing body of evidence on the use of self-testing in disease prevention and detection. However, we would not recommend self-testing for urine glucose and protein without further study.

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 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)0.018
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.031
GPT teacher head0.325
Teacher spread0.294 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations7
Published2022
Admission routes1
Has abstractyes

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