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Record W3076011784 · doi:10.21608/ejhc.2020.106958

Applying Health Belief Model among High Risk Hypertensive Clients

2020· article· en· W3076011784 on OpenAlexaboutno aff
Heba Abd El Hafiez Abd El Rhman, Magda Abd El-Sattar Ahmed, Sabah Radwan

Bibliographic record

VenueEgyptian Journal of Health Care · 2020
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHealth belief modelPopulationBlood pressureFamily medicineCompliance (psychology)Quarter (Canadian coin)Health educationNursingPublic healthPsychologyInternal medicineSocial psychologyEnvironmental health

Abstract

fetched live from OpenAlex

Background: Worldwide, recent reports indicate that more than one billion adults(more than a quarter of the world’s population) had hypertension, Aim: evaluation the effectof application (HBM) amongst high risk hypertensive clients. Research design: qausiexperimental design was used. Sample: included ten percent of total number 910 of clientswho attended on out-patient clinic in the previous year (214-2015). Setting: the study wasconducted at out patients' clinic of medicine affiliated to the Ain Shams University Hospital.Tools: three tools were used to collect data; the first tool: was a self-administeredquestionnaire for assessing socio-demographic characteristics of clients, and their knowledgeabout hypertension. Second tool: (HBM) related to hypertension. Third tool: physicallyassessment health status of clients measured (BP, pulse, weight, height). Results: studyindicated that more than half of hypertensive clients had unsatisfactory knowledge related tohypertension and near three fifth of them with higher percentage in female. Post health beliefmodel application, there was highly significant improvement in clients knowledge, attitude,and blood pressure. Conclusion: the study proved that used of HBM as framework thatguide and help improvement in client's knowledge, attitude, and health status.Recommendations: the study recommended that design and implement different educationalprograms based on HBM for hypertensive client's and regarding to needs assessment forhypertension (e.g.: definition, classification, causes, signs/symptoms, diagnostic methods,complication, methods of early detection of client's at high risk, management) to improve therate of compliance by improving client's consequences. Counseling hypertensive client'severy time whenever they visit to physician to improve the compliance to antihypertensivedrugs, therapeutic lifestyle modification, and other needed self-cares to control hypertension.Design and disseminate related booklets and brochures to raise client's knowledge regardinghypertension (detect, treating, controlling) as well the community social support network.Utilize different media channels such as T.V., to raise population awareness regardinghypertension, prevention and intervention.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.300
Teacher spread0.258 · 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 designNot applicable
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".

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Citations3
Published2020
Admission routes1
Has abstractyes

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