MétaCan
Menu
← Back to cohort
Record W2996231757 · doi:10.2196/15523

Increasing Awareness and Use of Mobile Health Technology Among Individuals With Hypertension in a Rural Community of Bangladesh: Protocol for a Randomized Controlled Trial

2019· article· en· W2996231757 on OpenAlexvenueno aff
Yasmin Jahan, Michiko Moriyama, Md Moshiur Rahman, Kana Kazawa, Atiqur Rahman, Abu Sadat Mohammad Sayeem Bin Shahid, Sumon Kumar Das, ASG Faruque, Mohammod Jobayer Chisti

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsmHealthMedicineRandomized controlled trialIntervention (counseling)Health educationHealth interventionPsychological interventionFamily medicineGerontologyEnvironmental healthPhysical therapyPublic healthNursingSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Hypertension remains one of the foremost noncommunicable diseases that most often lead to cardiovascular diseases and its different complications. The prevalence of hypertension in Bangladesh has been increasing. However, there are very limited studies that have evaluated the impact of health education and awareness development in mitigating the burden of hypertension and its complications in Bangladesh. OBJECTIVE: This study aims to increase awareness, enhance knowledge, and change lifestyle behaviors through health education and the use of mobile health (mHealth) technology among individuals with hypertension living in a rural community of Bangladesh. METHODS: A randomized controlled trial is underway in a Mirzapur subdistrict of Bangladesh. This trial compares two groups of individuals with hypertension: The comparison arm receives health education and the intervention arm receives health education and a periodic mobile phone-based text message intervention. The trial duration is 5 months. The primary end point is participants' actual behavior changes brought about by increased awareness and knowledge. RESULTS: Enrollment of participants started in August 2018, and collection of follow-up data was completed at the end of July 2019. A total of 420 participants volunteered to participate, and among them, 209 and 211 were randomly allocated to the intervention group and the control group, respectively. Among them, the ratio of males/females was 12.0/88.0 in the intervention group and 16.1/83.9 in the control group. Data cleaning and analyses have been completed and the results have been submitted for publication. CONCLUSIONS: Periodic short education using mHealth technology in addition to face-to-face health education may be an effective method for increasing awareness and knowledge about behavioral changes and maintaining healthy lifestyle behaviors. TRIAL REGISTRATION: Bangladesh Medical Research Council (BMRC) 06025072017; ClinicalTrials.gov NCT03614104, https://clinicaltrials.gov/ct2/show/NCT03614104; University hospital Medical Information Network (UMIN) R000033736, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_his_list.cgi?recptno=R000033736. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15523.

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)0.036
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.079
Threshold uncertainty score0.265

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.031
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0120.007
Bibliometrics0.0030.004
Science and technology studies0.0040.003
Scholarly communication0.0050.005
Open science0.0040.002
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0790.012

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 head0.231
GPT teacher head0.580
Teacher spread0.349 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations10
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Research Protocols→Same topicMobile Health and mHealth Applications→French-language works237,207→