Family fIRST, an <i>I</i> nteractive <i>R</i> isk <i>S</i> creening <i>T</i> ool for Families in a School-Based Pediatric Clinic
Bibliographic record
Abstract
The purpose of this study was to create a tablet-based, social history screening tool called Family fIRST and evaluate its feasibility and usability in a school-based medical clinic. A mixed methods study design was used to examine quantitative and qualitative outcomes of a survey and semi-structured interview completed by families and physicians. The majority (87%) found the survey easy to understand. Themes for improvement included more free-form space and increased sensitivity around question wording. Clinic physicians felt Family fIRST increased discussion around social history and suggested the tool should help link to suggested resources. Demographic results showed that 12 of 29 (43%) parents had income less than $15 000 and 19 of 29 (65%) were unemployed. Family fIRST was a well-received and feasible tool to implement at the school-based medical clinic. Preliminary results show that families attending the clinic have increased prevalence of negative determinants of health; social history should therefore represent a key area of focus at the medical visit in order to optimize clinic support of families.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".