The Framing Effect of Digital Textual Messages on Uptake Rates of Medical Checkups: Field Study
Notice bibliographique
Résumé
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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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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