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Record W4394614891 · doi:10.22442/jlumhs.2024.01043

Exploring the Lived Experience of Early Hypertension: Insights from Traditional Medicine Perspectives

2024· article· en· W4394614891 on OpenAlexaff
Aidin Aryankhesal, Roshanak Ghods, Asie Shojaii

Bibliographic record

VenueJournal of Liaquat University of Medical & Health Sciences · 2024
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsInstitute of Health Economics
FundersMinistry of Health and Medical EducationIran University of Medical Sciences
KeywordsMedicinePsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To elicit symptoms, risk factors, and habits existing before or right after blood pressure elevation in newly diagnosed patients with hypertension from the traditional Persian medicine perspective. METHODOLOGY: This was a concurrent nested mixed-method study conducted in 2018. We included newly diagnosed cases of hypertension (BP140/90 mmHg in two consecutive screenings) in the study. In contrast, those who had a history of hypertension or used anti-hypertension medication were excluded. The participants were surveyed and interviewed to identify their temperament and extract their recent experiences with hypertension. The sampling followed the criterion-based purposive technique, and the sample size was defined based on qualitative data saturation. The recorded interviews were transcribed and coded according to Persian medicine until no new code emerged. RESULTS: Twenty participants were interviewed, and two themes were extracted: (i) primary or predisposing factors, such as warm temperament, change of residence, improper eating habits, abrupt cessation of exercise, psychological factors, and irregular sleep patterns, and (ii) early symptoms that occur at the first sign of rising blood pressure, including digestive complaints and changes in body excretion, psychological manifestations, and unclassifiable general symptoms. CONCLUSION: Physicians are advised to pay attention to these items when taking a history from patients to prevent hypertension and treat it at its early stages.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.415
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.257
GPT teacher head0.344
Teacher spread0.087 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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