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Record W4400550426 · doi:10.1161/jaha.123.032568

Multiethnic Perspectives of Shared Decision‐Making in Hypertension: A Mixed‐Methods Study

2024· article· en· W4400550426 on OpenAlexaff
Sabrina Elias, Jennifer Wenzel, Lisa A. Cooper, Nancy Perrin, Yvonne Commodore‐Mensah, Krystina B. Lewis, Binu Koirala, Sarah Slone, Samuel Byiringiro, Jill A. Marsteller, Cheryl Dennison Himmelfarb, Rexford S. Ahima, Carmen Alvarez, Denis G. Antoine, Gideon D. Avornu, Jackie Bhattarai, Lee Bone, Romsai T. Boonyasai, Kathryn A. Carson, Jeanne Charleston, Suna Chung, Marcia Cort, Deidra C. Crews, Gail L. Daumit, Katherine B. Dietz, Teresa Eyer, Demetrius Frazier, Raquel C. Greer, Debra Hickman, Felicia Hill‐Briggs, Anika L Hines, Tammie Hull, Chidinma A. Ibe, Lawrence Johnson, Susan M. Johnson, Mary Kargbo, Mary Kelleher, Mariana Lazo, Lisa H. Lubomski, Lena Mathews, Edgar R. Miller, Chiadi E. Ndumele, Ruth‐Alma Turkson‐Ocran, Randy Parker, Cassandra Peterson, Tanjala S. Purnell, Natalie Spicyn, DeNotta Teagle, Nae‐Yuh Wang, Marcee White, Hsin‐Chieh Yeh, Joan K. Young, Kimberly L. Zeren

Bibliographic record

VenueJournal of the American Heart Association · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineContext (archaeology)Blood pressureEthnic groupMultinomial logistic regressionRelative riskLogistic regressionFamily medicineInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

Background Shared decision‐making (SDM) has the potential to improve hypertension care quality and equity. However, research lacks diverse representation and evidence about how race and ethnicity affect SDM. Therefore, this study aims to explore SDM in the context of hypertension management. Methods and Results Explanatory sequential mixed‐methods design was used. Quantitative data were sourced at baseline and 12‐month follow up from RICH LIFE (Reducing Inequities in Care of Hypertension: Lifestyle Improvement for Everyone) participants (n=1212) with hypertension. Qualitative data were collected from semistructured individual interviews, at 12‐month follow‐up, with participants (n=36) selected based on their SDM scores and blood pressure outcome. Patients were cross‐ categorized based on high or low SDM scores and systolic blood pressure reduction of ≥10 or <10 mm Hg. Multinomial logistic regression analysis showed that predictors of SDM scores and blood pressure outcome were race and ethnicity (relative risk ratio [RRR], 1.64; P =0.029), age (RRR, 1.03; P =0.002), educational level (RRR, 1.87; P =0.016), patient activation (RRR, 0.98; P <0.001; RRR, 0.99; P =0.039), and hypertension knowledge (RRR, 2.2; P <0.001; and RRR, 1.57; P =0.045). Qualitative and mixed‐methods findings highlight that provider–patient communication and relationship influenced SDM, being emphasized both as facilitators and barriers. Other facilitators were patients' understanding of hypertension; clinicians' interest in the patient, and clinicians' personality and attitudes; and barriers included perceived lack of compassion, relationship hierarchy, and time constraints. Conclusions Participants with different SDM scores and blood pressure outcomes varied in determinants of decision and descriptions of contextual factors influencing SDM. Results provide actionable information, are novel, and expand our understanding of factors influencing SDM in hypertension.

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)0.027
metaresearch head score (Gemma)0.028
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
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 head0.160
GPT teacher head0.508
Teacher spread0.347 · 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
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
Published2024
Admission routes1
Has abstractyes

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