The Childhood Immunization Reminder Project (ChIRP): A pilot test of text message immunization reminders to improve immunization attendance in Alberta, Canada (Preprint)
Bibliographic record
Abstract
BACKGROUND Vaccine coverage for 18-month-old children in Canada is often below recommended levels, which may be partially due to parental forgetfulness. Text message reminders have been shown to potentially improve childhood immunization uptake, but were not widely utilized in Alberta, Canada. Additionally, it has been noted that language barriers may impede immunization service delivery but continue to be unaddressed in many existing reminder/recall systems. OBJECTIVE We aimed to assess the effectiveness and acceptability of using text messages, containing a link to online immunization information in different languages, to remind parents of their child’s 18-month immunization appointment. METHODS The Childhood Immunization Reminder Project (ChIRP) was a pilot intervention at two public health centres, one each in Lethbridge and Edmonton, Alberta, Canada. Two text message reminders were sent to parents: (1) a booking reminder 3 months before their child turned 18 months old, and (2) an appointment reminder three days before their scheduled appointment. Booking reminders included a link to the study website hosting immunization information in nine languages. To evaluate the intervention effectiveness, we compared absolute attendance no-show rates pre- and post-intervention. Acceptability of the intervention was evaluated through online surveys completed by parents and public health centre staff. Google Analytics was used to determine how often the online immunization information was accessed, from where, and in which languages. RESULTS Following the intervention, the Edmonton health centre had a reduction of 6.4% (95% CI: 3.0, 9.8) in appointment no-shows, with no change at the Lethbridge health centre (0.8%; 95% CI: -1.4, +3.0). Acceptability surveys were completed by 222 parents (response rate: 23.9%) and 22 staff. Almost all (>95%) respondents indicated that the reminders were helpful and had useful suggestions for improvements. All surveyed parents (100.0%) found it helpful to read the online immunization information in their language of choice. Google Analytics data showed that the immunization information was most often read in English (57.0%), Punjabi (25.1%), Arabic (6.3%), Spanish (5.8%), Italian (1.9%), Chinese (1.9%), French (1.0%), Tagalog (0.5%), and Vietnamese (0.5%). CONCLUSIONS The study findings support the use of text message reminders as a convenient and acceptable method to minimize parental forgetfulness and potentially reduce appointment no-shows. The diverse languages accessed in the online immunization information suggest the need to provide appropriate translated immunization information. Further research is needed to evaluate the impact of text message reminders on childhood immunization coverage in different settings.
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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".