Assessment and intervention

The requirements of assessment are generally straightforward, encompassing a small number of question types, with conditional branching logic to skip over unnecessary questions. However, interventionsand appropriate ways to trigger them are more difficult to define.

Separate from the blocks specification, but still an integral part of Jeeves, is the Survey Creation Pane, shown in Figure 5.6. This drag-and-drop interface was designed from a review of existing EUD-ESM tools, as well as online tools for survey creation such asSurveyMonkeyandQualtrics. Different question types can be customised with a simple form. The current implementation supports conditional branching on previous answers, and the ability to store a participant’s question response as the value of an attribute, as shown in Figure 5.5. The reason for such

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Figure 5.6: A screenshot of the Jeeves Survey Design pane

features are explained in the following requirements.

Requirement 5 - Jeeves must support a variety of survey question types

The types of question asked in psychology and clinical research are free-text questions, single selection questions, multi-selection questions, and Likert scale questions. Variations of such questions are also necessary (for example, questions restricted to numbers, or true/false questions). Jeeves provides additional question types that store dates, times, locations, and heart rate.

Requirement 6 - Jeeves must support conditional branching based on question responses

To minimise the burden on participants, it is necessary for EUD-ESM tools to implement some form of branching that jumps over irrelevant questions according to a participant’s response to an earlier question. In Figure 5.6, the left side shows the variety of available question types, with the middle showing questions currently integrated in the selected survey. The darker shade of the top two questions (Box A) shows that these questions are related. The indentation of the lower question denotes that it is conditional on the answer to its predecessor.

Certain question types require additional customisation (Box B). For example, Likert scale questions can have a variety of labels, and the variance in the scale differs considerably between

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studies. The conditional branching function can be seen (Box C), whereby certain questions with predictable answers within a range (such as those with numeric responses, or responses from a set list of options) can act as branching questions that determine whether future questions are asked. In the Figure 5.6 example, the Likert scale question is only asked if the response to the numeric question is more than 5.

Requirement 7 - Jeeves should support tailored interventions

The requirement for intervention capabilities in research and clinical practice is particularly salient, yet is not addressed in current EUD-ESM tools. In Heron and Smyth’s seminal paper on ecological momentary interventions (EMIs) they describe intervention feedback that could be delivered on a number of conditions [75]:

1. On completion of an experience sampling survey 2. Prompted by a participant in response to an event 3. Triggered in response to external context

The intervention content, in both psychology research and clinical practice, typically consists of a supportive message or provision of information. While less appropriate in controlled research studies, practice-based interventions can also solicit the involvement of an external individual, such as a carer or a healthcare provider. The ability for an app to communicate with a chosen contact is a desirable feature for particular contexts (such as apps for monitoring heart failure or other life-threatening conditions [89]). Thus, information prompts should be deliverable to both a study participant, and to suitable contacts with a stake in the participant’s well-being.

Heron and Smyth further describe how mobile implementations can “allow for the timing of messages to be individually tailored by providing EMI at specific times when participants or patients are most in need of additional support” [75, p. 3]. In doing so, participants are more likely to respond favourably to an intervention, and seek this support with minimal delay. Table 5.4 describes three Jeeves implementations of example interventions, which include a number of different blocks beyond the basic introduced triggers and actions. While the trigger blocks are used to represent discrete events, the if-condition and expression blocks are used to represent continuous, ongoing state - a conceptual difference explained by Ur et al. [159]. Thus, Jeeves supports tailored intervention delivery throughevent-state interventions. The lower two examples demonstrate this combination of event and state. The discrete, one-timeevent(such as a participant entering a new location or completing a survey) does not alone warrant execution of intervention actions. However, if the participant is in a particularstateat the time of the event, represented by the if-conditionand its conditional expression, then the intervention actions

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Table 5.4: Types of intervention and their Jeeves representation

Sampling

Strategy RepresentationJeeves

User presses a ‘panic button’, SMS is sent to an emergency contact

User arrives home. If they have not taken their medication, a reminder prompt should be sent

User completes glucose assessment. If their reading is above a defined

value, a message is sent to the participant and emergency contact

should be executed. These two block types are further described.

5.2.3.1 If-Conditions

In combination with triggers, if-condition blocks specify additional constraints under which to execute an action. The notch on the if-condition block shows that it acts as a form of action, and can be logically nested within triggers. Unlike other actions, if-conditions have their own receiver for further action blocks that should be conditionally executed. This also means that if-condition blocks can be nested within one another indefinitely, an example of which is shown in the lower-left of Figure 5.7. To determine whether the nested actions of an if-condition are executed, the constraint is represented by an expression block.

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Figure 5.7:Expression blocks reduce the verbosity of the blocks paradigm

5.2.3.2 Expressions

Expression blocks are used to translate various user attributes into Boolean expressions. (The expressions available for each attribute type are shown in Table 5.3.) Additionally, they can function to simplify complex conditions, thereby reducing the number of if-condition blocks required. For example, Figure 5.7 shows how theand expression and theorexpression in the top two conditions can be used to represent the multiple conditions below it.