Repeated Automated Mobile Text Messaging Reminders for Follow-Up of Positive Fecal Occult Blood Tests: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Fecal occult blood tests (FOBTs) are recommended by the US Preventive Services Task Force as a screening method for colorectal cancer (CRC), but they are only effective if positive results are followed by colonoscopy. Surprisingly, a large proportion of patients with a positive result do not follow this recommendation. OBJECTIVE: The objective of this study was to examine the effectiveness of text messaging (short message service, SMS) in increasing adherence to colonoscopy follow-up after a positive FOBT result. METHODS: This randomized controlled trial was conducted with patients who had positive CRC screening results. Randomization was stratified by residential district and socioeconomic status (SES). Subjects in the control group (n=238) received routine care that included an alert to the physician regarding the positive FOBT result. The intervention group (n=232) received routine care and 3 text messaging SMS reminders to visit their primary care physician. Adherence to colonoscopy was measured 120 days from the positive result. All patient information, including test results and colonoscopy completion, were obtained from their electronic medical records. Physicians of study patients completed an attitude survey regarding FOBT as a screening test for CRC. Intervention and control group variables (dependent and independent) were compared using chi-square test. Logistic regression was used to calculate odds ratios (ORs) and 95% CIs for performing colonoscopy within 120 days for the intervention group compared with the control group while adjusting for potential confounders including age, gender, SES, district, ethnicity, and physicians' attitude. RESULTS: Overall, 163 of the 232 patients in the intervention group and 112 of the 238 patients in the control group underwent colonoscopy within 120 days of the positive FOBT results (70.3% vs 47.1%; OR 2.17, 95% CI 1.49-3.17; P<.001); this association remained significant after adjusting for potential confounders (P=.001). CONCLUSIONS: A text message (SMS) reminder is an effective, simple, and inexpensive method for improving adherence among patients with positive colorectal screening results. This type of intervention could also be evaluated for other types of screening tests. TRIAL REGISTRATION: ClinicalTrials.gov NCT03642652; https://clinicaltrials.gov/ct2/show/NCT03642652 (Archived by WebCite at http://www.webcitation.org/74TlICijl).
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How this classification was reachedexpand
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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".