Text4Health: Impact of Text Message Reminder–Recalls for Pediatric and Adolescent Immunizations
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
OBJECTIVES: We conducted 2 studies to determine the impact of text message immunization reminder-recalls in an urban, low-income population. METHODS: In 1 study, text message immunization reminders were sent to a random sample of parents (n = 195) whose children aged 11 to 18 years needed either or both meningococcal (MCV4) and tetanus-diphtheria-acellular pertussis (Tdap) immunizations. We compared receipt of MCV4 or Tdap at 4, 12, and 24 weeks with age- and gender-matched controls. In the other study, we compared attendance at a postshortage Haemophilus influenzae B (Hib) immunization recall session between parents who received text message and paper-mailed reminders (n = 87) and those who only received paper-mailed reminders (n = 87). RESULTS: Significantly more adolescents with intervention parents received either or both MCV4 and Tdap at weeks 4 (15.4% vs 4.2%; P < .001), 12 (26.7% vs 13.9%; P < .005), and 24 (36.4% vs 18.1%; P < .001). Significantly more parents who received both Hib reminders attended a recall session compared with parents who only received a mailed reminder (21.8% vs 9.2%; P < .05). After controlling for age, gender, race/ethnicity, insurance status, and language, text messaging was still significantly associated with both studies' outcomes. CONCLUSIONS: Text messaging for reminder-recalls improved immunization coverage in a low-income, urban population.
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 | 0.003 | 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) | 0.000 | 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