Discussion
Despite good coverage for routine childhood vaccines in Australia, under-vaccination remains a challenge, and strategies to improve vaccine uptake and timeliness are still required to prevent transmission of preventable infectious diseases. Here, we propose a unique resource-efficient adaptive study that contains almost complete digital automation of trial processes, including eligibility screening, randomisation, delivery of the intervention, data capture and regular analyses with trial adaptations. We believe this may be the most digitally automated trial ever undertaken globally and, we anticipate, will become an exemplar for implementing embedded adaptive trials in primary care.
Given the risks and consequences of under-vaccination and delayed vaccination, it is important to identify effective ways of increasing vaccine uptake at both a local and national level [
16]. While much effort has been invested in strategies to motivate vaccination among hesitant parents, for many parents, simply reminding them when vaccines are due using SMS reminders may be a cheap, effective and implementable strategy at a large scale. The effectiveness of an SMS reminder plausibly depends on different factors, such as who the message is from, the framing of the message, and the timing of message relative to the vaccine due date.
Previous studies have found high acceptance among parents for vaccine reminders via SMS [
17‐
23], with one reporting that parents preferred receiving SMS reminders over telephone calls or letters [
22]. Although these data support the use of SMS reminders, they have largely come from studies in specific sub-populations (for example urban, low-income parents) and from the USA where recipients typically pay to receive messages; therefore, these studies may not be generalisable to a whole-of-population intervention outside the USA.
Most parents report that their GP is their most important source for information about vaccination [
2]. Data also show that parents trust information from healthcare providers such as GPs, with a personal recommendation from a GP being a strong driver of the decision to vaccinate [
24]. Accordingly, we hypothesise that an SMS sent by a child’s GP (or usual vaccine provider) might be an effective way to drive vaccine uptake and may be more effective than a message sent from another source, such as a government health department. This study will therefore evaluate messages issued by those vaccine providers.
To our knowledge, no studies to date have yet examined the influence of different message framing strategies in the context of SMS reminders on routine childhood vaccine uptake. In some contexts, a risk-framed message which appeals to potential harm arising from failure to act (like risk of contracting a preventable infection) can be effective [
25], but in other contexts, these messages may have either little effect or may paradoxically associate the harm with the desired behaviour itself [
26].
We are also not aware of previous studies examining the influence of multiple timing options on the effectiveness of SMS reminders for childhood vaccination. Sending an SMS vaccine reminder to all parents before the scheduled date might afford them sufficient time to organise vaccination, but reminders that are issued too early may be less effective for motivating action. Targeting parents of children who have already passed the scheduled due date may be most effective for motivating action, and if shown to be as or more effective than earlier reminders, may greatly reduce costs while also minimising burdensome reminders on parents who do not require them.
In summary, this adaptive trial will examine the effectiveness of SMS reminders on vaccine uptake and timeliness for routine childhood vaccination. Evaluating different health messaging strategies using simple SMS may serve as one effective aspect within a multimodal program for influencing vaccine acceptance and behaviour.
Trial status
At the time of this submission, 5462 parents have been randomised in the trial, with 5370 index cases. The first scheduled analysis was performed in August 2021. The anticipated date for completion of enrolment is December 2023.
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