Using a Mobile Health Intervention (DOT Selfie) With Transfer of Social Bundle Incentives to Increase Treatment Adherence in Tuberculosis Patients in Uganda: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: The World Health Organization's End TB Strategy envisions a world free of tuberculosis (TB)-free of deaths, disease, and suffering due to TB-by 2035. Nonadherence reduces cure rates, prolongs infectiousness, and contributes to the emergence of multidrug-resistant TB (MDR-TB). Moreover, MDR-TB is a growing, complex, and costly problem that presents a major obstacle to TB control. Directly observed therapy (DOT) for treatment adherence monitoring is the recommended standard; however, it is challenging to implement at scale because it is labor-intensive. Mobile health interventions can facilitate remote adherence monitoring and minimize the costs and inconveniences associated with standard DOT. OBJECTIVE: The study aims to evaluate the effectiveness of using video directly observed therapy (VDOT) plus incentives to improve medication adherence in TB treatment versus usual-care DOT in an African context. METHODS: The DOT Selfie study is an open-label, randomized controlled trial (RCT) with 2 parallel groups, in which 144 adult patients with TB aged 18-65 years will be randomly assigned to receive the usual-care DOT monitoring or VDOT as the intervention. The intervention will consist of a smartphone app, a weekly internet subscription, translated text message reminders, and incentives for those who adhere. The participant will use a smartphone to record and send time-stamped encrypted videos showing their daily medication ingestion. This video component will directly substitute the need for daily face-to-face meetings between the health provider and patients. We hypothesize that the VDOT intervention will be more effective because it allows patients to swallow their pills anywhere, anytime. Moreover, patients will receive mobile-phone-based "social bundle" incentives to motivate adherence to continued daily submission of videos to the health system. The health providers will log into a secured computer system to verify treatment adherence, document missed doses, investigate the reasons for missed doses, and follow prespecified protocol measures to re-establish medication adherence. The primary endpoint is the adherence level as measured by the fraction of expected doses observed over the treatment period. The main secondary outcome will be time-to-treatment completion in both groups. RESULTS: This study was funded in 2019. Enrollment began in July and is expected to be completed by November 2020. Data collection and follow-up are expected to be completed by June 2021. Results from the analyses based on the primary endpoint are expected to be submitted for publication by December 2021. CONCLUSIONS: This random control trial will be among the first to evaluate the effectiveness of VDOT within an African setting. The results will provide robust scientific evidence on the implementation and adoption of mobile health (mHealth) tools, coupled with incentives to motivate TB medication adherence. If successful, VDOT will apply to other low-income settings and a range of chronic diseases with lifelong treatment, such as HIV/AIDs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04134689; http://clinicaltrials.gov/ct2/show/NCT04134689. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/18029.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".