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Being Mindful About Motivation: How Mindfulness Apps for Anxiety Support Behaviour Change

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Being Mindful About Motivation: How Mindfulness Apps for Anxiety Support Behaviour Change

Extended abstract that explores how mindfulness apps apply motivation theories

Context

From January to April 2018, I explored mindfulness apps (mainly meditation apps) through the lenses of motivation theories (i.e. Self-determination theory) and positive computing. The primary research was supported by surveys, auto-ethnographic approaches and systematic reviews. This project was part of my MSc Human-Computer Interaction, Accessibility and Assistive Technologies module.

This article summarises a University assignment paper. You can check the original paper with in depth analysis and references as PDF.

Abstract

Extensive research shows that mindfulness-based interventions can be highly effective when it comes to dealing with anxiety. Ubiquitous computing has made it possible for people seeking to overcome anxiety to easily access such interventions through their smartphone. However, some studies indicated that users tend to have inconsistent patterns of use and often lead to abandonment because of lack of motivation. In an era where positive computing emerges, it is important to address the motivational aspect of health interventions. In this study we take an auto-ethnographic approach to help inform evaluation of the motivation aspects applied in mindfulness apps through the lens of Self-Determination Theory. We thereby propose a set of design implications and future refinements.

How can tech help with anxiety?

Anxiety disorders and depression have become the most prevalent mental disorders, with 1 in 6 people reporting having experienced them within the UK. Over the last years, there has been an interest into assistive technologies that focus on wellbeing, stress management and exercise in the human-computer interaction (HCI) area, more specifically in affective computing and positive computing.

Positive Computing

The term "positive computing" was proposed as an emerging design approach that aims to be as influential as human-centred design (HCD). This is introduced because, despite technology’s potential to enable users to achieve goals easier and have access to unlimited information, therefore improve lives, there has not been an improvement in their psychological wellbeing. The effects are rather detrimental in this aspect.

This concept draws on Seligman and Csikszentmihalyi’s positive psychology which focuses on human wellbeing and aims to uncover what makes people’s life worth living though valued subjective experiences. Another basis of positive computing is Desmet et al. subjective wellbeing which aspires to act as an enabler and focus on the quality of human life, taking into account life aspirations and needs.

Ryan and Deci further argue about the construct of wellbeing, which draws from two perspectives: the hedonic approach (wellbeing as experience of emotions) and the eudaemonic approach (wellbeing as self-realisation and one’s potential), and stress that intrinsic motivation such as enjoyment enhances wellbeing in contrast to extrinsic goals such as financial success.

Digital interventions for anxiety disorders

Psychological interventions were proven to be effective for reducing anxiety symptoms together with medication or instead of it. These can include cognitive behavioural therapy (CBT), relaxation training or mindfulness interventions. Mindfulness interventions have been successful in reducing anxiety symptoms.

The overwhelming flow of information people experience is highly influenced by technology and can have a negative impact on mental health. On the other hand, as ubiquitous technologies emerge, they provide new opportunities for health and wellbeing interventions. Mobile apps can be a cost-effective way of accessing healthcare. Features such as push notifications, text and media content can make mobile devices suitable for the delivery of mental health interventions. Therefore, mindfulness interventions are increasingly used in the context of treatment of anxiety.

Behaviour change and motivation

Failure to design interventions that stimulate intrinsic motivation can inhibit behaviour change and make users abandon health technologies. Self-Determination Theory (SDT) in the context of health intervention focuses on the motivation an individual acquires to adopt a new health-related behaviour. SDT embraces the concept of eudaimonia and intrinsic motivation as the core of wellbeing.

There are three psychological aspects that are crucial for psychological growth and overall wellbeing and can lead to long-term behaviour changes. These are autonomy, competence and relatedness. In the Self-Determination Health Behaviour Model, each of these pillars is applied in the context of health.

Pilot Study: mindfulness apps are the preferred way to cope with anxiety

I conducted a pilot study to find out what technologies people use to help them cope with anxiety. The questionnaire revealed that mindfulness mobile apps are the most prevalent. This infomed the course of the study and its focus on mindfulness apps.

Using Headspace to identify motivational aspects

I conducted a 30 day auto-ethnography on Headspace. The aim was not to generalize findings, as it is subjective in its nature, but rather to inform further study design decisions and app evaluation. Some motivational aspects that I identified during this process:

  1. Gamification of app: streaks, stats of time meditated, sessions completed, and goals
  2. Daily reminders or calendar event (opt-in feature): reminder time could be set by the user
  3. Mindful messages through push notifications to help the user stay mindful
  4. Design to offer a sense of progress: record of all sessions by day, days in pack were numbered and content was prioritised, so the user could start from where they were left
  5. Prioritisation of content so that the user can resume from where they were left off
  6. Advice on how to create a routine for meditation through animations and during sessions
  7. Information about both meditation and anxiety was reassuring of the overall process
  8. Instructor reassuring users that good meditation skill takes time and what they might experience
  9. Displaying the number of people currently meditating offered a sense of "social support"

Looking at mindfulness apps through the Self-Determination Theory lenses

The data gathered so far offered a good insight into how to design the app evaluation scale. This scale was based on the Self-determination theory, and its three pillars: autonomy, competence, relatedness. The apps reviewed were Headspace, Calm, Breethe, and Simple Habit. All were upgraded to premium trial to allow full access.

Please refer to the paper if you’d like to see the in-depth discussion about the method and its findings.

Conclusion: Implications for design

Best practices found in the apps to facilitate motivation and behaviour change were:

Push notifications: reminders are useful in order to persuade the user; however, Headspace also offered the "mindful moments" feature which can help remind the user multiple times through the day about mindfulness and persuade them to keep meditating. It also offered an event creation in the calendar rather than a reminder, which can increase autonomy by allowing the user to choose how they want to be reminded to be mindful.

Stats: most apps offered stats in different forms that could be interpreted more or less at glance; Personal informatics are crucial for people to be able to reflect on their activity and visualise their progress, hence promoting behaviour change.

Information and layout: all apps were not targeted to anxiety only, offering other support as well (i.e. for sleeping). Categorising and prioritising content can make it easier for users to select the right meditation for them. Information about what the session is about helps users feel more confident with their choice, which increases autonomy and competence. Headspace organises its sessions in packs, which are put in different categories. This allows users to choose what they want to target better. In contrast, Breethe categorises collections by recommended or most popular, which is not necessarily efficient. For example, users with anxiety might want to find the right meditation for anxiety, rather than what most people use.