ArticleJAMA network open2021
Factors Associated With Opting Out of Automated Text and Telephone Messages Among Adult Members of an Integrated Health Care System.
Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- The Impact of Dose in an mHealth Intervention to Support Parents and Carers Via Healthy Beginnings for Hunter New England Kids Program: Pragmatic Randomized Controlled Trial.JMIR formative research · 2025Trial
- Population-Based Digital Health Interventions to Deliver at-Home COVID-19 Testing: SCALE-UP II Randomized Clinical Trial.Journal of medical Internet research · 2025Trial
- An Interactive Voice Response System for Postoperative Care in Primary Total Joint Arthroplasty Patients: A Pilot Study.Applied clinical informatics · 2025Trial
- Pragmatic Randomized Study of Targeted Text Message Reminders to Reduce Missed Clinic Visits.The Permanente journal · 2022Trial
- Automated Health Care Messages and Unexpected Patient Responses.JAMA network open · 2026Article
- Pandemic fatigue and associated factors: a meta-analysis using the COM-B model.Frontiers in psychology · 2026Review
- Tailoring dengue health communication: Survey-based strategies to reduce message fatigue across risk areas.PLoS neglected tropical diseases · 2025Article
- A digital health intervention to support patients with chronic pain during prescription opioid tapering: a pilot randomised controlled trial.Pain reports · 2024Article
- Developing Patient-Centered Communication Ecosystems in Integrated Health Care Delivery Organizations.The Permanente journal · 2023Article
- Analyzing User Engagement Within a Patient-Reported Outcomes Texting Tool for Diabetes Management: Engagement Phenotype Study.JMIR diabetes · 2022Article
- Implementing Automated Text Messaging for Patient Self-management in the Veterans Health Administration: Qualitative Study Applying the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability Framework.JMIR mHealth and uHealth · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Health care systems deliver automated text or telephone messages to remind patients of appointments and to provide health information. Patients who receive multiple messages may demonstrate message fatigue by opting out of future messages. Objective: To assess whether the volume of automated text or interactive voice response (IVR) telephone messages is associated with the likelihood of patients requesting to opt out of future messages. Design, Setting, and Participants: This retrospective cohort study was conducted at Kaiser Permanente Colorado (KPCO), an integrated health care system. All adult members who received 1 or more automated text or IVR message between October 1, 2018, and September 30, 2019, were included. Exposures: Receipt of automated text or IVR messages. Main Outcomes and Measures: Message volume and opt-out rates obtained from messaging systems over 1 year. Results: Of the 428 242 adults included in this study, 59.7% were women, and 66.5% were White; the mean (SD) age was 52.3 (17.7) years. During the study period, 84.1% received 1 or more text messages (median, 4 messages; interquartile range, 2-8 messages) and 67.8% received 1 or more IVR messages (median, 3 messages; interquartile range, 1-6 messages). A total of 8929 individuals (2.5%) opted out of text messages, and 4392 (1.5%) opted out of IVR messages. In multivariable analyses, individuals who received 10 to 19.9 or 20 or more text messages per year had higher opt-out rates for text messages compared with those who received fewer than 2 messages per year (adjusted odds ratio [aOR]: 10-19.9 vs <2 messages, 1.27 [95% CI, 1.17-1.38]; ≥20 vs <2 messages, 3.58 [95% CI, 3.28-3.91]), whereas opt-out rates increased progressively in association with IVR message volume, with the highest rates among individuals who received 10.0 to 19.9 messages (aOR, 11.11; 95% CI, 9.43-13.08) or 20.0 messages or more (aOR, 49.84; 95% CI, 42.33-58.70). Individuals opting out of text messages were more likely to opt out of IVR messages (aOR, 4.07; 95% CI, 3.65-4.55), and those opting out of IVR messages were more likely to opt out of text messages (aOR, 5.92; 95% CI, 5.29-6.61). Conclusions and Relevance: In this cohort study among adult members of an integrated health care system, requests to discontinue messages were associated with greater message volume. These findings suggest that, to preserve the benefits of automated outreach, health care systems should use these messages judiciously to reduce message fatigue.
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