Is opt-out enrolment acceptable for low-risk digital health services?
Rosie Dobson
1 2 * , Amanda Uri 1 3 , Robyn Whittaker 1 2 , Karen Evison 4 , Elaine Umali 1 , Hayden McRobbie 4
1 National Institute for Health Innovation, University of Auckland, Auckland, Aotearoa New Zealand.
2 Te Whatu Ora – Waitematā, Auckland, Aotearoa New Zealand.
3 Te Arawa Whānau Ora, Rotorua, Aotearoa New Zealand.
4 Te Whatu Ora – Lakes, Rotorua, Aotearoa New Zealand.
Journal of Primary Health Care 14(4) 368-371 https://doi.org/10.1071/HC22088
Published: 14 October 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of The Royal New Zealand College of General Practitioners. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
Introduction: Digital health programmes not only complement existing services, but have the potential to reach populations that existing services are not reaching. Many of these services require people to opt-in to receive them, which presents significant barriers to access. An alternative is to make low-risk digital services opt-out, ensuring appropriate members of the target audience are signed up for a service unless they select to not receive it.
Aim: This study aimed to investigate how changing enrolment in a low-risk digital health programme from opt-in to opt-out would impact on enrolment and dropout rates.
Methods: This study involved the retrospective analysis of registration data from txtpēpi, a maternal and child health text-message programme. System-recorded data from enrolments during a 12-month period were obtained. In the first 6 months, users had to opt-in to the service (Period 1), but in the following 6 months, an opt-out process was implemented (Period 2).
Results: There was a 77% increase in enrolments in Period 2 (n = 113) compared to Period 1 (n = 64) and no significant change in the proportion of enrolments of Māori between time periods (P = 0.508). There was no significant difference in withdrawal rates between time periods at either 2 weeks (5% vs 6%, P = 0.676) or 1 month (9% vs 9%, P = 0.907).
Discussion: This study has shown switching from an opt-in to an opt-out option resulted in an increase in enrolments in an mHealth programme, but had no impact on withdrawals. This indicates that employing opt-out enrolment for low-risk evidence-based interventions is acceptable and a potential way to make these services more accessible.
Keywords: child health, digital health, maternal health, mobile phone, mHealth, short message service, SMS, text messages.
References
[1] Reid P, Robson B. Understanding health inequities. In: Hauora: Māori Standards of Health IV. A study of the years 2000–2005. (Eds P Reid, B Robson). Wellington: Te Ròpù Rangahau Hauora a Eru Pòmare; 2007. pp. 3–10.[2] Wikaire E, Harwood M, Wikaire-Mackey K, et al. Reducing healthcare inequities for Māori using Telehealth during COVID-19. N Z Med J 2022; 135 112–9.
[3] Whittaker R, McRobbie H, Bullen C, et al. Mobile phone text messaging and app-based interventions for smoking cessation. Cochrane Database Syst Rev 2019; CD006611
| Mobile phone text messaging and app-based interventions for smoking cessation.Crossref | GoogleScholarGoogle Scholar |
[4] Dobson R, Whittaker R, Jiang Y, et al. Effectiveness of text message based, diabetes self management support programme (SMS4BG): two arm, parallel randomised controlled trial. BMJ 2018; 361 k1959
| Effectiveness of text message based, diabetes self management support programme (SMS4BG): two arm, parallel randomised controlled trial.Crossref | GoogleScholarGoogle Scholar |
[5] Willcox J, Wilkinson S, Lappas M, et al. A mobile health intervention promoting healthy gestational weight gain for women entering pregnancy at a high body mass index: the txt4two pilot randomised controlled trial. BJOG 2017; 124 1718–28.
| A mobile health intervention promoting healthy gestational weight gain for women entering pregnancy at a high body mass index: the txt4two pilot randomised controlled trial.Crossref | GoogleScholarGoogle Scholar |
[6] Thakkar J, Kurup R, Laba TL, et al. Mobile telephone text messaging for medication adherence in chronic disease: a meta-analysis. JAMA Intern Med 2016; 176 340–9.
| Mobile telephone text messaging for medication adherence in chronic disease: a meta-analysis.Crossref | GoogleScholarGoogle Scholar |
[7] Bramley D, Riddell T, Whittaker R, et al. Smoking cessation using mobile phone text messaging is as effective in Maori as non-Maori. N Z Med J 2005; 118 U1494
[8] Willcox JC, Dobson R, Whittaker R. Old-fashioned technology in the era of “bling”: is there a future for text messaging in health care? J Med Internet Res 2019; 21 e16630
| Old-fashioned technology in the era of “bling”: is there a future for text messaging in health care?Crossref | GoogleScholarGoogle Scholar |
[9] Oakes AH, Epstein JA, Ganguly A, et al. Effect of opt-in vs opt-out framing on enrollment in a COVID-19 surveillance testing program: the COVID SAFE randomized clinical trial. JAMA Netw Open 2021; 4 e2112434
| Effect of opt-in vs opt-out framing on enrollment in a COVID-19 surveillance testing program: the COVID SAFE randomized clinical trial.Crossref | GoogleScholarGoogle Scholar |
[10] Mehta SJ, Khan T, Guerra C, et al. A randomized controlled trial of opt‐in versus opt‐out colorectal cancer screening outreach. Am J Gastroenterol 2018; 113 1848–54.
| A randomized controlled trial of opt‐in versus opt‐out colorectal cancer screening outreach.Crossref | GoogleScholarGoogle Scholar |
[11] Aysola J, Tahirovic E, Troxel AB, et al. A randomized controlled trial of opt-in versus opt-out enrollment into a diabetes behavioral intervention. Am J Health Promot 2018; 32 745–52.
| A randomized controlled trial of opt-in versus opt-out enrollment into a diabetes behavioral intervention.Crossref | GoogleScholarGoogle Scholar |
[12] Dobson R, Whittaker R, Bartley H, et al. Development of a culturally tailored text message maternal health program: TextMATCH. JMIR Mhealth Uhealth 2017; 5 e49
| Development of a culturally tailored text message maternal health program: TextMATCH.Crossref | GoogleScholarGoogle Scholar |
[13] Campbell KA, Cooper S, Fahy SJ, et al. ‘Opt-out’ referrals after identifying pregnant smokers using exhaled air carbon monoxide: impact on engagement with smoking cessation support. Tob Control 2017; 26 300–6.
| ‘Opt-out’ referrals after identifying pregnant smokers using exhaled air carbon monoxide: impact on engagement with smoking cessation support.Crossref | GoogleScholarGoogle Scholar |
