Mobile phone–based clinical guidance for rural health providers in India
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There are few tried and tested mobile technology applications to enhance and standardize the quality of health care by frontline rural health providers in low-resource settings. We developed a media-rich, mobile phone-based clinical guidance system for management of fevers, diarrhoeas and respiratory problems by rural health providers. Using a randomized control design, we field tested this application with 16 rural health providers and 128 patients at two rural/tribal sites in Tamil Nadu, Southern India. Protocol compliance for both groups, phone usability, acceptability and patient feedback for the experimental group were evaluated. Linear mixed-model analyses showed statistically significant improvements in protocol compliance in the experimental group. Usability and acceptability among patients and rural health providers were very high. Our results indicate that mobile phone-based, media-rich procedural guidance applications have significant potential for achieving consistently standardized quality of care by diverse frontline rural health providers, with patient acceptance.
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.
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 | 0.023 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 it