Health Education Through a Campaign and mHealth to Enhance Knowledge and Quality of Life Among Patients With Chronic Kidney Disease in Bangladesh: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Despite the growing burden of chronic kidney disease (CKD), disease knowledge and understanding are still lacking, especially in Bangladesh. OBJECTIVE: The aim of this study was to evaluate the outcome of a health education intervention in order to enhance knowledge, health-related quality of life (QOL), and motivation regarding healthy lifestyles among rural and periurban adults suffering from CKD. METHODS: A parallel-group (1:1) randomized controlled trial is ongoing in the Mirzapur subdistrict, Bangladesh, where two groups of patients with CKD are being compared. Patients aged 18 years and over with CKD (stages 1-3) were enrolled in November 2020. Patients were randomly allocated into either the intervention group (n=63) or the control group (n=63). The control group received usual treatment, while the intervention group received health education through a CKD campaign facilitated by a nephrologist and via mHealth (ie, periodic mobile phone calls) from community health workers. Both groups were followed up for a period of 6 months. The primary endpoint is patients' increased knowledge measured using the Chronic Kidney Disease Knowledge Questionnaire. The secondary endpoints are improved QOL measured using the standardized EuroQol 5-Dimension 5-Level (EQ-5D-5L) questionnaire as well as improvements in the levels of blood pressure, BMI, serum creatinine, fasting blood sugar, hemoglobin, cholesterol, high-density lipoprotein cholesterol, triglyceride, serum uric acid, blood urea nitrogen, and albumin to creatinine ratio. RESULTS: Enrollment of participants began in November 2020; the intervention and follow-up were completed in May 2021. We enrolled 126 patients in the study. Patients' mean ages were 57.97 (SD 15.03) years in the control group and 57.32 (SD 14.37) years in the intervention group. There were 45 out of 63 (71%) females in the control group and 38 out of 63 (60%) females in the intervention group. In addition, there were 38 out of 63 (60%) literate patients in the control group and 33 out of 63 (52%) literate patients in the intervention group. CONCLUSIONS: It is expected that a combined approach, incorporating both a CKD campaign and mHealth, for health education may be an effective tool for increasing knowledge and improving QOL among patients with CKD. TRIAL REGISTRATION: ClinicalTrials.gov NCT04094831; https://clinicaltrials.gov/ct2/show/NCT04094831. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30191.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.021 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.055 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".