Mobile health for early retention in HIV care: a qualitative study in Kenya (WelTel Retain)
Bibliographic record
Abstract
Many people newly diagnosed with HIV are lost to follow-up before timely initiation of antiretroviral therapy (ART). A randomised controlled trial (RCT), WelTel Kenya1, demonstrated the effectiveness of the WelTel text messaging intervention to improve clinical outcomes among patients initiating ART. In preparation for WelTel Retain, an RCT that will evaluate the effect of the intervention to retain patients in care immediately following HIV diagnosis, we conducted an informative qualitative study with people living with HIV (n = 15) and healthcare providers (HCP) (n = 5) in October 2012. Study objectives included exploring the experiences of people living with HIV who have attempted to engage in HIV care, the use of cell phones in everyday life, and perceptions of communicating via text message with HCP. Participants were recruited through convenience sampling. Semi-structured, qualitative interviews were conducted and recorded, transcribed verbatim and analysed using NVivo software. Analysis was guided by the Theory of Reasoned Action and the Technology Acceptance Model. Results indicate that while individuals have many motivators for engaging in care after diagnosis, structural and individual barriers including poverty, depression and fear of stigma prevent them from doing so. All participants had access to a mobile phone, and most were comfortable communicating through text messages, or were willing to learn. Both people living with HIV and HCP felt that increased communication via the text messaging intervention has the potential to enable early identification of problems, leading to timely problem solving that may improve retention and engagement in care during the first year after diagnosis.
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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 | 0.017 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; 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".