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Record W2560120056 · doi:10.1177/0145721716679276

Understanding Financial Barriers to Care in Patients With Diabetes

2016· article· en· W2560120056 on OpenAlexaff
David J.T. Campbell, Braden Manns, Brenda R. Hemmelgarn, Claudia Sanmartin, Alun Edwards, Kathryn King‐Shier

Bibliographic record

VenueThe Diabetes Educator · 2016
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
Fundersnot available
KeywordsThematic analysisVariety (cybernetics)Health careGrounded theoryMedicineDiabetes mellitusNursingBusinessQualitative researchFamily medicineFinancePolitical science

Abstract

fetched live from OpenAlex

Purpose The purpose of this study was to better understand the impact that financial barriers have on patients with diabetes and the strategies that they use to cope with them. Methods A secondary analysis was conducted of 24 interviews with patients who had either type 1 or type 2 diabetes and perceived financial barriers, which were previously undertaken for a larger grounded theory study. Semistructured interviews were undertaken either face-to-face or by telephone. Data analysis was performed by 3 reviewers using inductive thematic analysis. Sampling for the original study continued until data saturation was achieved. Results The predominant aspects of care to which participants described financial barriers were medications, diabetes supplies, and healthy food. A variety of strategies are used by these patients. Participants described that their health care providers had the potential to either play an important supporting role; or alternatively, that they could also worsen the impacts of financial barriers. Conclusions Patients with diabetes experience financial barriers to various aspects of their care. While they use a variety of strategies to overcome their barriers, their health care providers can play a particularly important role in helping them manage these important barriers that impact their care and outcomes. Providers should ask patients about the existence of financial barriers, and employ strategies to mitigate against their impact.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.333
Teacher spread0.298 · 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

Citations55
Published2016
Admission routes1
Has abstractyes

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