Health App Review Tool (HART): Content validation through expert panel review
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
The Health App Review Tool (HART) is an evaluation tool that is designed to help the users in evaluation of the health apps for Alzheimer's Disease and Related Dementias (ADRD) population. As the development of the HART continues, the domain items that HART addresses require evaluation to determine if they meet the intended required criteria for the users.To complete content validation of the HART 10 health care professions provided content validation of the HART via a content validation form. Specifically, data collection took place virtually through Microsoft Teams and Qualtrics-based content validity index. Following, revisions were made through a consensus process involving 3 rehabilitation experts, minimizing potential conflicts.Findings indicate 76 of 109 items were considered acceptable, 19 items were in need of review and 14 items in need of revision. In sum 30% of the total HART items required either review or revision to improve HART validity. The changes were implemented through consensus revisions.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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