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Record W4385357542 · doi:10.36367/ntqr.16.2023.e785

“When I Don’t Have Money, I Don’t Eat”: A Critical Hermeneutic Study of Diabetes in Liberia

2023· article· en· W4385357542 on OpenAlexafffund
Paulina Bleah, Rosemary Wilson, Danielle Macdonald, Pilar Camargo‐Plazas

Bibliographic record

VenueNew Trends in Qualitative Research · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsQueen's University
FundersQueen's University
KeywordsPhotovoiceGerontologyDiabetes mellitusPsychological interventionMedicinePublic healthPopulationHealth careFaithSocioeconomic statusEnvironmental healthPolitical scienceNursingEconomic growth

Abstract

fetched live from OpenAlex

Diabetes is a growing public health concern in Liberia, where an estimated 2.1% of the population live with the disease. The challenges with diabetes in Liberia are enormous. Diabetes places immense socioeconomic pressure on individuals and their families and burdens an already overstretched health care system still recovering from the destructive effects of the 14-year civil war. While efforts towards rebuilding the health care system in Liberia are ongoing, people with diabetes experience significant challenges accessing social, economic, and health-care resources to manage their illness. Purpose: The goal of this critical hermeneutic study was to explore what is it like to live with diabetes in Liberia. Methods: Through purposeful sampling, 10 adults with diabetes were recruited from a publicly funded hospital in Monrovia, Liberia. Data were collected using a photovoice method, wherein participants photographed their everyday experiences of living with diabetes. Results: We identified three themes that answered the question of what is it like to live with diabetes in Liberia: living with diabetes means living with 1) food insecurity, 2) trying to access a health care system that was not built to respond to diabetes, and 3) using faith to cope and foster hope. Conclusion: The experiences of people living with diabetes in Liberia are under-researched, pointing to a gap in knowledge. The findings from this study address this gap in the literature by providing a clearer picture of the impact of diabetes on individuals and families. We provide tangible recommendations to local governments and policy makers on interventions that may improve health outcomes and quality of life for people living with diabetes in Liberia.

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)0.011
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.290
GPT teacher head0.542
Teacher spread0.252 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2023
Admission routes2
Has abstractyes

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