Barriers and facilitators of implementing electronic monitors to improve adherence and health outcomes in tuberculosis patients: protocol for a systematic review based on the Consolidated Framework for Implementation Research
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) has been regarded as 'a relentless scourge', increasing morbidity and mortality and burdening vulnerable populations. Poor adherence to TB treatment and ineffective traditional interventions hinders TB control. A novel TB approach called 'electronic monitors', equipping medication boxes with daily audio or visual reminders for electronically monitoring medication intake, seems promising in improving adherence and health outcomes and overcoming the weaknesses of traditional interventions. However, no review has systematically examined and synthesized the influencing factors of implementing electronic monitors. Implementation research offers the means to analyse the influencing factors of the implementation and its process, fitting well with the aim of this review. Therefore, the widely recognized Consolidated Framework for Implementation Research (CFIR), which offers a common taxonomy for evaluating intervention implementation, will be adopted to systematically identify barriers and facilitators of the electronic monitors for improving adherence and health outcomes in patients with TB. METHODS AND ANALYSIS: The systematic review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Literature research will be conducted in five electronic databases (Ovid MEDLINE, CINAHL, EMBASE, Cochrane Library and Web of Science) to identify the barriers and facilitators of implementing electronic monitors in patients with TB. The CFIR will be used as a guide for categorizing and synthesizing the barriers and facilitators. Study screening, data extraction, quality appraisal and data analysis will be conducted by two independent reviewers. The use of additional reviewers will solve any disagreements between the two reviewers. DISCUSSION: Given the increased prominence of TB epidemiology and the adherence problem of electronic monitors, there is a solid rationale for synthesizing the existing studies via the CFIR. The findings and conclusion of this review will lay bare the achievements and effectiveness of implementing electronic monitors, as well as the attendant gaps and limitations. Further strategies for facilitating the implementation of electronic monitors will also be explored. This review will be of essential significance for research and practice, supporting future academic research initiatives centred on patients with TB and aiding electronic monitor design in lowering the morbidity and mortality associated with TB disease. TRIAL REGISTRATION NUMBER: PROSPERO: CRD42023395747.
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 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 | 0.059 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".