Digital Health Screening in People With HIV in Uganda to Increase Alcohol Use Reporting: Qualitative Study on the Development and Testing of the Self-administered Digital Screener for Health
Bibliographic record
Abstract
BACKGROUND: Alcohol consumption is a critical driver of the HIV epidemic worldwide, particularly in sub-Saharan Africa, where unhealthy alcohol use and HIV are prevalent. Brief alcohol interventions are effective in reducing alcohol use; however, they depend on effective screening for unhealthy alcohol use, which is often underreported. Thus, there is a need to develop methods to improve reporting of unhealthy alcohol use as an essential step toward referral to brief alcohol interventions. Self-administered digital health screeners may improve reporting. OBJECTIVE: This study aimed to develop and test a digital, easy-to-use self-administered health screener. The health screener was designed to be implemented in a busy, underresourced HIV treatment setting and used by patients with varying levels of literacy. METHODS: We conducted a qualitative study at the Immune Suppression Syndrome (ISS) Clinic of Mbarara Regional Referral Hospital in Uganda to develop and test a digital self-administered health screener. The health screener included a training module and assessed behaviors regarding general health, HIV care, and mental health as well as sensitive topics such as alcohol use and sexual health. We conducted focus group discussions with clinicians and patients with HIV of the Mbarara ISS Clinic who consumed alcohol to obtain input on the need for and content, format, and feasibility of the proposed screener. We iteratively revised a tablet-based screener with a subset of these participants, piloted the revised screener, and conducted individual semistructured in-depth interviews with 20 participants who had taken part in our previous studies on alcohol and HIV, including those who had previously underreported alcohol use and with low literacy. RESULTS: A total of 45 people (n=5, 11% clinicians and n=40, 89% Mbarara ISS Clinic patients) participated in the study. Of the patient participants, 65% (26/40) were male, 43% (17/40) had low literacy, and all (40/40, 100%) had self-reported alcohol use in previous studies. Clinicians and patients cited benefits such as time savings, easing of staff burden, mitigation of patient-provider tension around sensitive issues, and information communication, but also identified areas of training required, issues of security of the device, and confidentiality concerns. Patients also stated fear of forgetting how to use the tablet, making mistakes, and losing information as barriers to uptake. In pilot tests of the prototype, patients liked the feature of a recorded voice in the local language and found the screener easy to use, although many required additional help and training from the study staff to complete the screener. CONCLUSIONS: We found a self-administered digital health screener to be appealing to patients and clinicians and usable in a busy HIV clinic setting, albeit with concerns about confidentiality and training. Such a screener may be useful in improving reporting of unhealthy alcohol use for referral to interventions.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".