The development of effective interventions for COVID-19 vaccination has proven challenging given the unique and evolving determinants of that behavior. A tailored intervention to drive vaccination uptake through machine learning-enabled personalization of behavior change messages unexpectedly yielded a high volume of real-time short message service (SMS) feedback from recipients. A qualitative analysis of those replies contributes to a better understanding of the barriers to COVID-19 vaccination and demographic variations in determinants, supporting design improvements for vaccination interventions. Objective: The purpose of this study was to examine unsolicited replies to a text message intervention for COVID-19 vaccination to understand the types of barriers experienced and any relationships between recipient demographics, intervention content, and reply type. Method: We categorized SMS replies into 22 overall themes. Interrater agreement was very good (all κpooled . 0.62). Chi-square analyses were used to understand demographic variations in reply types and which messaging types were most related to reply types. Results: In total, 10,948 people receiving intervention text messages sent 17,090 replies. Most frequent reply types were “already vaccinated” (31.1%), attempts to unsubscribe (25.4%), and “will not get vaccinated” (12.7%). Within “already vaccinated” and “will not get vaccinated” replies, significant differences were observed in the demographics of those replying against expected base rates, all p . .001. Of those stating they would not vaccinate, 34% of the replies involved mis-/disinformation, suggesting that a determinant of vaccination involves nonvalidated COVID-19 beliefs. Conclusions: Insights from unsolicited replies can enhance our ability to identify appropriate intervention techniques to influence COVID-19 vaccination behaviors.

An in-depth analysis of replies to COVID-19 vaccination outreach reveals thanks, angst — and much more.

This highlights some really important things to consider in creating behavior change interventions - there isn't one “user journey“ - as Amy said many times, personalization will matter (and we can have a whole other conversation on what personalization means). There may be a “dose“ effect for some people where they need to accumulate a certain understanding before any message works and it is more about the dose than the personalization (or not) of the most proximal message.

Out of the 93 behavior change techniques that can be used, on average only 7 were chosen, and the most common were related to: 1. Feedback on behavior 2. Goal setting 3. Action planning As the study says: “within the “Goals and Planning” BCT group, only 3 out of 9 BCTs were utilized.

Digital media are omnipresent in modern life, but the science on the impact of digital media on behavior is still in its infancy. There is an emerging evidence base of how to use digital media for behavior change. Strategies to change behavior implemented using digital technology have included a variety of platforms and program strategies, all of which are potentially more effective with increased frequency, intensity, interactivity, and feedback. It is critical to accelerate the pace of research on digital platforms, including social media, to understand and address its effects on human behavior. The purpose of the current paper is to provide an overview and describe methods in this emerging field, present use cases, describe a future agenda, and raise central questions to be addressed in future digital health research for behavior change. Digital media for behavior change employs three main methods: (1) digital media interventions, (2) formative research using digital media, and (3) digital media used to conduct evaluations. We examine use cases across several content areas including healthy weight management, tobacco control, and vaccination uptake, to describe and illustrate the methods and potential impact of this emerging field of study. In the discussion, we note that digital media interventions need to explore the full range of functionality of digital devices and their near-constant role in personal self-management and day-to-day living to maximize opportunities for behavior change. Future experimental research should rigorously examine the effects of variable levels of engagement with, and frequency and intensity of exposure to, multiple forms of digital media for behavior change.

Designing Health & Fitness Apps with the Mind in Mind - Massimo Ingegno (and other speakers)

Emotions and worries can reduce individuals’ available attention and affect economic decisions. In a four-week experiment with 2,384 US adults, offering free access to a popular mindfulness meditation app (Headspace) that costs $13 per month improves mental health, productivity and decisionmaking. First, it causes a 0.44 standard deviation reduction in symptoms of stress, anxiety, and depression, comparable to the impacts of expensive in-person therapy, with improvements even among participants with minimal or mild symptoms at baseline. Second, it increases earnings on a proofreading task by 1.9 percent. Third, it makes decision-making more stable across emotional states, reducing the interference of personal worries with risk choices. Overall, our results demonstrate the potential of affordable mindfulness meditation apps to improve mental health, productivity, and the impact of emotions on economic decisions.

When the growth team took a step back, they realized it wasn’t enough to trigger just any notification. They needed to “show the right things to users at the right time — creating ‘aha moments’” where the user experienced the product’s core value. Rather than indiscriminately bombard the user with notifications, they concluded that they needed to be “really thoughtful about which messages to send which users” and focus “more of [their] resources on engaging users that were likely to churn.” Taking a page from Facebook, here are 5 kinds of engagement messages that work to activate, retain, and grow customers. Highly personal and targeted, these emails show off your product’s core value, ferry your users to their “aha moments”, and get people engaging with your product and brand again and again.

demand for depression drugs is also witnessing a decline as end-users have more coping options at their disposal. The huge popularity of mental health apps, such as Headspace, Calm, Moodnotes, Pacifica, and SuperBetter has given patients more control over how they manage depression.

Luckily, behavioral science can help close the intention-action gap, offering a toolkit to help change behavior for the better. Here are three ways we can apply lessons from behavioral science to drive sustainable engagement:

“Tracking your daily activity with a pedometer, wearable, or smartphone is an important part of any physical activity program,” Patel said by email. “However, it should be combined with other behavior change strategies such as goal-setting, coaching, or social interventions to increase sustainability.”

This group of papers on the use of mobile phones in India for social and behaviour change is the product of research and a two-day multi-stakeholder consultation in May 2013 sponsored by the United Nations Children's Fund (UNICEF) and the Digital Empowerment Foundation (DEF), leading to the formation of the organisation Mobile Social & Behavioural Change (MSBC). The white paper and the working paper present key areas where mobiles are contributing to social and behavioural changes and the limitations, as well as the scope, for expanding the social space for mobiles. The case studies paper is based upon examples of "mobile’s power to trigger new form[s] of social identity, including cultural, political and economic identities."