Effectiveness and Acceptability of Targeted Text Message Reminders in Colorectal Cancer Screening: Randomized Controlled Trial (M-TICS Study)
Bibliographic record
Abstract
BACKGROUND: Mobile phone-based SMS text message reminders have the potential to improve colorectal cancer screening participation rates. OBJECTIVE: This study assessed the effectiveness and acceptability of adding targeted SMS text message reminders to the standard procedure for those who picked up but did not return their screening kit at the pharmacy within 14 days in a colorectal cancer screening program in Catalonia, Spain. METHODS: We performed a randomized control trial among individuals who picked up a fecal immunochemical test (FIT) kit for colorectal cancer screening at the pharmacy but did not return it within 14 days. The intervention group (n=4563) received an SMS text message reminder on the 14th day of kit pick up and the control group (n=4806) received no reminder. A 30-day reminder letter was sent to both groups if necessary. The main primary outcome was the FIT completion rate within 30, 60, and 126 days from FIT kit pick up (intention-to-treat analysis). A telephone survey assessed the acceptability and appropriateness of the intervention. The cost-effectiveness of adding an SMS text message reminder to FIT completion was also performed. RESULTS: The intervention group had higher FIT completion rates than the control group at 30 (64.2% vs 53.7%; P<.001), 60 (78.6% vs 72.0%; P<.001), and 126 (82.6% vs 77.7%; P<.001) days. Participation rates were higher in the intervention arm independent of sex, age, socioeconomic level, and previous screening behavior. A total of 339 (89.2%) interviewees considered it important and useful to receive SMS text message reminders for FIT completion and 355 (93.4%) preferred SMS text messages to postal letters. We observed a reduction of US $2.4 per participant gained in the intervention arm for invitation costs compared to the control arm. CONCLUSIONS: Adding an SMS text message reminder to the standard procedure significantly increased FIT kit return rates and was a cost-effective strategy. SMS text messages also proved to be an acceptable and appropriate communication channel for cancer screening programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04343950; https://www.clinicaltrials.gov/study/NCT04343950. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1371/journal.pone.0245806.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".