Interruption policies

Interruption policies enable “do-not-disturb” capability for notifications during a set time period, extending the historical device-wide silent mode by providing application- level policies. While notifications still arrive as usual, the associated audio, and haptic cues are suppressed. Policies can either silence all notifications or be more selective towards specific applications. Figure 6.9 shows the distribution of users who set an interruption policy at least once.

The results show that the majority of users (𝑛= 2345, 75.5%) did not use an interruption policy at all, suggesting that manually managing these may be undesirable. In these cases, users only suppressed interruptions by setting the device to a global vibrate rule (if at all), where the audio cues of all notifications are silenced but vibrate and visual cues still occur. For those that did adopt interruption policies (𝑛 = 761, 24.5%), the majority of these (𝑛= 627, 82.4%) only applied selective policies that only allow the audio and haptic cues from specific notifications (e.g., only alarms). A small number of users (𝑛= 100, 13.1%) only used policies that silence all notifications, and a few users used both types (𝑛= 34, 4.5%). API restrictions and privacy permissions prevent the exploration of individual rules, however, the results indicate that users are generally not using Android’s built in interruption policies.

Going forward, this also raises the question as to what other cognitive mechanisms are being used to manage notifications. This forms a key focus in the analysis of

128 6.2 Flexibility of the DOIG model

Using Not using

Use of policies 0 500 1000 1500 2000 2500 Number of users

Figure 6.9: Use of interruption policies across users.

notification behaviour in general in Chapter 7. In particular, whether other conscious or subconscious mechanisms can be exposed from behavioural patterns across the independent responses to individual notifications.

6.2.2.3 Impact on observable decisions in the DOIG Model

The variability in device preferences surrounding notifications and interruption policies illustrate that the DOIG model needs to be flexible to these, in addition to the notification design choices of applications. Firstly, the largest potential impact on the DOIG response process comes from users being able to display information about notifications on the lock-screen (Figure 6.8). The ability for this to occur was introduced in Android 5.0 and therefore only needs to be considered for this Android version and above. In this case, the second and third decisions representing engageability and receptivity when the device is not in use (D2 and D3, shown in Chapter 3, Figure 3.2) will need to be merged if the notification priority is normal or higher (otherwise they are not shown immediately on the lock screen). This is because the user no longer needs to unlock the device to view the notification summary. However, if notifications are not shown on the

6.2 Flexibility of the DOIG model 129

lock-screen, or if they contain private content that is concealed by the application, then this does not have an effect on the observable decisions (i.e., the response process is similar to Android versions < 5.0).

The other settings have more minor effects on the observable decisions of the DOIG model. Applications that use LED patterns as part of their explicit interruptive cues would need to consider whether the LED is available when determining whether reach- ability and engageabilty is likely to be distinguishable (as discussed in Section 6.2.1.4). Finally, the ability for high priority notifications to popup on the screen while it is in use has little effect. This is because the decision process is already challenging to observe while the device is in use (as discussed in Chapter 3, Section 3.2.2).

Notification policies can also impact the DOIG model for notifications that have audible or haptic cues. If a policy is in effect that suppresses these cues then this affects whether a response may occur. While it does not change the response process to the same extent as notification display preferences, it does impact whether the user is in a position to be reachable. However, including this consideration is challenging for two reasons. Firstly, even if an interruption policy is not in effect, an application cannot know if a user is simply not reachable or that they were not interrupted (as discussed in Chapter 3, Section 3.2.2.1). Secondly, a typical application will likely not have access to whether a policy is in effect. Notification policy access is an additional permission that is unlikely to fit with the design of most applications, likewise to the notification access through the NotificationListener API.

Summary: Notification characteristics and user preferences are highly

variable

Overall, the analysis has highlighted how the DOIG model can be flexible to the vari- ability that can exist in notification design and display preferences, supporting the discussions of the conceptual flexibility in Chapter 3, Section 3.2.2.1. However, in in-

130 6.3 Conclusions

vestigating this, a secondary but independent set of primary findings can be summarised as:

• Notifications are diverse in their design, in addition to their individual content and purpose;

• Notifications are not synonymous with interruptions;

• The use of different on-board notification related preferences suggest that user’s wish to control the visibility of notifications;

• The absence of interruption policies for most users suggests that other conscious or sub-conscious management mechanisms may be in effect.

Collectively, these findings highlight the extent to which mobile notifications have evolved from telephonic and alarm based interruptions, and that they now form an integral part of mobile device usage. However, these findings do not highlight the extent to which notifications punctuate our daily lives or the processes used to manage the volume and diversity.

6.3

Conclusions

Android’s flexibility in the way notifications operate and can be managed provides degrees of freedom to both application developers issuing notifications and to users receiving them. The strategy adopted in this thesis is to embrace this by creating a flexible labelling framework that is capable of considering this variability and then able maximise, as far as possible, the ability to capture decision making in interruption response behaviour. Chapter 3 has discussed this theoretically, and the analysis of the empirical Boomerang Notifications data set in this chapter supports this further, forming the following thesis contribution:

6.3 Conclusions 131

designs and device preferences, using additional in-the-wild data.

Going forward, the findings of variability in the use of interruption policies and noti- fication display settings (Section 6.2.2) suggests that other, wider (conscious or sub- conscious) management processes for notifications may exist. This forms the primary focus of the next chapter, in exploring the existence of decision making behaviour in how notifications are managed from the wider viewpoint of the notification stack, in order to further support the DOIG model.

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Chapter 7

Coexisting Notifications

While individual mobile notifications occur independently of one another, they can coexist and subsequently build up into a “stack” where they compete for attention (shown in Figure 7.1). Using the Boomerang Notification dataset introduced in Chapter 6, the purpose of this chapter is to explore further design considerations for the DOIG model, through analysing the extent to which notifications coexist together, whether decision behaviour in notification responses can be seen from this wider viewpoint, and how this coexistence can impact the decision processes surrounding notification consumption.

The rationale for examining interaction behaviour with notifications that coexist together (as opposed to the viewpoint of individual notifications in isolation) is discussed further in Section 7.1, leading to the introduction of the concept of the notification stack in Section 7.2. Following this, response behaviour towards notifications from the viewpoint of the notification stack is examined in Section 7.3, with the impact of the presence of other notifications on individual responses explored in Section 7.4. Finally, the impact on the DOIG model is discussed in Section 7.5, towards the final conclusions of this thesis.