User engagement in the tuberculosis treatment support tools intervention and its impact on treatment outcomes: A secondary analysis of a pragmatic trial
Data files
Jun 09, 2026 version files 29.28 KB
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engagement_dataset_updated_per_requirements_6.6.26.csv
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README.md
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Abstract
Digital adherence technologies (DATs) may improve health behaviors only when users engage, but links between engagement, user factors, and outcomes are unclear. TB Treatment Support Tools (TB-TST) is a DAT with a smartphone app connecting patients to treatment supporters and weekly drug metabolite testing. We evaluated TB-TST app engagement in a pragmatic randomized controlled trial and identified factors associated with adherence and treatment outcomes.
Engagement was measured from app interactions (n=277) over 180-days of TB treatment. Adherence was assessed via daily self-reports dosing and weekly metabolite-test photo submissions. Participants could also message supporters and report side effects or request help. We modeled time to non-adherence (28 consecutive days without reporting) using survival analysis. Logistic regression tested associations of adherence and engagement with treatment outcomes. A latent engagement score was derived using confirmatory factor analysis (CFA) from medication reports, photo submissions, side-effect reports, messaging, and overall adherence. Participants submitted 24,902 medication reports, 2,926 messages, 2,465 photos, 1235 side effect reports, and 128 help requests. Adherence declined over time (78% at 60 days; 50% at 180 days). Non-adherence was more common among males, participants living at or below the poverty line, those without stable employment, and those treated at certain hospitals. Non-adherence was associated with lower odds of treatment success (OR 0.48, 95% CI: 0.22 - 0.94) and higher odds of loss to follow-up (OR 2.1, 95% CI: 1.03 - 4.7), adjusting for sex, age, education, income, and employment. Higher engagement scores were associated with higher odds of success (OR 2.2 times per standard deviation increase).
Engagement with TB-TST was associated with improved TB treatment outcomes. Strategies to increase and sustain engagement, particularly among high-risk groups, may improve adherence and maximize DAT benefits.
Dataset DOI: 10.5061/dryad.x3ffbg7zj
Description of the data and file structure
We evaluated engagement with the Tuberculosis Treatment Support Tools (TB-TST) app tested in a pragmatic randomized controlled trial to identify factors associated with adherence and treatment outcomes.
Files and variables
File: engagement_dataset_updated_per_requirements_6.6.26.csv
Description:
Variables
- ID: Randomly generated ID
- gender: gender
- age: age
- argentina: From study country (Argentina)
- stable_job: employment stable
- outcome: TB treatment outcome
- success: Treatment outcome: success
- default_lost: Treatment outcome: Lost to follow up
- num_of_msgs: Number of messages sent
- requests_for_help: Number of requests for help
- n_photos_submitted: Number of photos submitted of drug metabolite test
- n_severe_symptoms: Number of severe symptoms
- severe_sideeffect: Number of severe side effects
- non_adherent_14: Non-adherence of 14 consecutive days
- daysto_nonadherance_14: Number of days in treatment to non-adherence of 14 consecutive days
- exited_treatment_before_180days_: exited treatment before 180 days
- non_adherent_28: Non-adherence of 28 consecutive days
- daysto_nonadherance_28: Number of days in treatment to non-adherence of 28 consecutive days
- total_reports: Total number of days reported self-administration of treatment
- hospital 1: Hospital 1 or other
- deviation: Deviation in study protocol (e.g., drug resistance identified, treatment change)
- side_effect: Having any side effects
- income_cat: Income category
- adherent_28: Adherent (no 28 consecutive days of non-reporting)
- engagement_score: Engagement score
Code/software
Excel
Access information
Other publicly accessible locations of the data:
- n/a
Data was derived from the following sources:
- n/a
Human subjects data
Explicit consent from participants was obtained to store and share a final dataset stripped of individual identifiers to share or submit to a repository for further research to understand how to improve TB outcomes. The dataset has been de-identified. It does not identify any individual that is a subject of the data and does not provide any reasonable basis for identifying any individual that is a subject of the data.
