Informing Facility Selection Through a Web-Based User Ratings System: Protocol for a Randomized Controlled Trial Among Mothers in Urban Lao People’s Democratic Republic
Bibliographic record
Abstract
BACKGROUND: Despite the increasing options for public and private health care providers in the Lao People's Democratic Republic (Lao PDR), choosing a high-quality provider or facility is difficult because timely and reliable information about providers is not readily available. Additionally, only 28% described their most recent visit to a health care provider as high quality, suggesting that while options for care are expanding, people may need support in finding providers that meet their quality needs. To inform efforts to improve access to high-quality care, evidence is needed on mechanisms that empower people to identify and use such care. The rapid adoption of mobile phones in Lao PDR, particularly in urban areas, offers opportunities to enhance access to timely, reliable information about health care facilities. OBJECTIVE: This study aims to conduct an unblinded randomized controlled experiment using mobile phones to study whether routinely collected information on quality of care can improve access to high-quality care and patient satisfaction. METHODS: Mothers with at least one child under 2 years of age who are already enrolled in the Vientiane Multigenerational Birth Cohort (VITERBI) will be invited to participate during in-person visits by the research staff. Participants will be randomly assigned in equal numbers to the control and intervention groups. The intervention group will receive a URL with facility ratings for pediatric health care services every 2 weeks via WhatsApp; the control group will not receive any messages. WhatsApp will also be used to administer biweekly surveys to both groups to assess the quality of care received in the past 2 weeks. The web page shared with the intervention group will display results from these surveys and from the pilot study. Research staff will conduct baseline and endline surveys with all participants during in-person visits, 3 months apart. RESULTS: The trial is currently underway and scheduled for completion in 2025. CONCLUSIONS: This study will use a demand-side intervention to increase demand for high-quality child health care among mothers in Vientiane Capital. We will assess whether information on the quality of health care facilities-generated by study participants during the study period-influences mothers to change their preferred providers for nonurgent conditions. TRIAL REGISTRATION: ClinicalTrials.gov NCT06304831; https://www.clinicaltrials.gov/study/NCT06304831. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/66085.
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 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 | 0.036 | 0.031 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.061 | 0.009 |
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".