The Framing Effect of Digital Textual Messages on Uptake Rates of Medical Checkups: Field Study
Bibliographic record
Abstract
BACKGROUND: Health care authorities often use text messages to enhance compliance with medical recommendations. The effectiveness of different message framings has been studied extensively over the past 3 decades. Recently, health care providers have begun using digital media platforms to disseminate health-related messages. OBJECTIVE: This study aimed to examine the effectiveness of some of the most widely used message framings on the uptake rates of medical checkups. METHODS: This study used a large-scale digital outreach campaign conducted by Maccabi Healthcare Services (MHS) during 2020-2021, involving a total of 113,048 participants. MHS members aged 50-74 years were invited to take their recommended medical actions from the following list: human papillomavirus (HPV), mammography, abdominal aortic aneurysm, fecal occult blood test (FOBT), and pneumococcal vaccination. Each member was randomly assigned to receive 1 of 6 message framings: control (neutrally framed; n=20,959, 18.5%), gains (benefits of compliance; n=20,393, 18%), losses (negative consequences of noncompliance; n=15,165, 13.4%), recommendation (a recommendation by an authoritative figure, in this context by a physician; n=20,584, 18.2%), implementation intentions (linking potential outcomes to future reactions; n=20,701, 18.3%), and empowerment (emphasizing personal responsibility for maintaining good health; n=15,246, 13.5%). The time frames for measuring a successful intervention were 14 days for scheduling screenings (ie, HPV, mammography, or abdominal aortic aneurysm), 30 days for performing the FOBT, and 60 days for receiving pneumococcal vaccination. We also examined the effectiveness of media channels (text message or email) on uptake rates and whether the subject-line length is correlated with message-opening rates. RESULTS: No significant effect of message framing on uptake rates of medical checkups was observed. The rates of appointments for screening ranged from 12.9% to 14.1% across treatments. Based on a chi-square test, there was no evidence to reject the null hypothesis that these compliance rates are independent of the treatments (P=.35). The uptake rates for the FOBT and pneumococcal vaccination ranged from 23.3% to 23.8% across treatments, and we could not reject the hypothesis that they are independent of the treatments (P=.88). We also found that emails are more effective than text messages (P<.001) and that the subject-line length is negatively correlated with message-opening rates. CONCLUSIONS: No evidence was found for an effect of the 5 message framings on uptake rates of medical checkups. To enhance compliance rates, public health officials may consider alternative framings. Furthermore, media channels and the subject-line length should be given careful consideration in the planning stages of health care campaigns. TRIAL REGISTRATION: AEA RCT Registry AEARCTR-0006317; https://www.socialscienceregistry.org/trials/6317/history/201365.
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".