Smart interventions

www.minddistrict.com

Bridging the gap: Smart interventions to overcome obstacles of traditional cognitive behavioral therapy

By Maurice Niessen Research manager, Minddistrict

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Over the past decade and a half, cognitive behavioural therapy (CBT) based online interventions have been developed for a wide variety of mental health disorders. Although effective, these in-terventions have yet to fully address the limitations of traditional CBT, known as the ‘knowledge to practice gap’ and the ‘therapy to real world gap’. Recent innovations however suggest that mo-bile applications will soon overcome these obstacles by delivering real-time, personalised CBT.

In the past, mental health professionals that offered traditional face-to-face CBT to their clients had to overcome the difficulties of personalising CBT protocols to each client, and assisting the client in implementing cognitive and behavioural strategies in their everyday lives. Nowadays, therapists are already much better equipped to reduce the gap between the therapist’s office and real-life. The modern therapist’s toolbox consists of face-to-face contacts, video conferencing and secure messaging. In addition, websites and mobile applications are available to deliver psychological educational material, homework exercises and diaries. Together, these tools have the potential to make interventions become a seamless part of day-to-day life enabling clients to access care whenever and wherever they choose.

Real-time data collectionRecently, there has been an increased focus on investigating experiences outside the therapy office, in the context in which they are occuring. A powerful rationale for this approach is provided by a growing awareness that models of psychopathology are dynamic over time and experiences are situated. The experience sampling method (ESM) is a data collection strate-gy in which individuals are asked in normal daily life to report their thoughts, feelings and symptoms, as well as the context (e.g. location, company, activity) and their judgement of this context. The reports typically have to be filled out several times a day, on consecutive days, either at random unpre-dictable moments, at moments signalled by a beeper or alternatively, trigge-red by an event of interest. The mobile revolution has propelled ESM studies over recent years and has triggered some to commence developing ESM based interventions. Amsterdam based Minddistrict is one of these compa-nies.

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MinddistrictIn the Netherlands, two out of three mental health care institutions already apply ehealth in their care provisions or communication with patients. The vision of Dutch ehealth market leader Minddistrict is to facilitate lasting be-havioural change by providing effective and cost-effective, seamless ehealth solutions. For this purpose, Minddistrict has developed an easy-to-use, secure online platform in which interventions can be dynamically tailored to the current needs of an individual client. The platform contains eviden-ce-based CBT modules for the prevention, early intervention, treatment and aftercare of a wide variety of mental health disorders which can be implemented with varying levels of professional guidance (self-help, guided self-help, psychotherapy). In addition to the treatment modules, screening, secure messaging and video chat can be offered to the client on his or her personalised platform which is connected to a mobile diary app.

From insight to automated interventionThe ESM is incorporated into Minddistrict’s diary app. Graphs are included to provide a detailed insight into the daily course of thoughts, feelings, symp-toms and their context. Displayed in the diary app, the real-time graphs help to create awareness for the patient. The therapist is able to view the same graphs in his or her secure online platform. Recent studies suggest that the ESM can also be utilised to deliver personalised, automated, in-the-mo-ment, ‘smart’ interventions. Minddistrict agrees with this assessment and has outlined its three-stage ‘smart’ intervention development plan. At each progressing stage, increasing levels of intelligence are added to the inter-vention.

In the first stage, clients complete a brief assessment of their current emoti-onal status in response to a random sound trigger on Minddistrict’s mobile diary app with multiple choice touchscreen response options. The respon-ses determine the nature of the subsequent intervention they will receive. Supportive messages are displayed in response to reported negative emoti-ons and reaffirming thoughts are depicted when the client indicates positive affect. These automated messages have multiple wording variations so that clients do not encounter the exact same intervention every time, even if they make similar selections. Also, all intervention content can be accessed whenever and wherever clients choose.

In addition, in the second stage, correlations between context and emotions

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are calculated to determine personal protective and risk factors. To create awareness, these insights are reported to the user and therapist. Emotion mining, or the automated identification of emotions by analysing patterns in users’ texts, is utilised for groups of clients who lack the ability to identify or decribe their emotional state or situational context. Emotion mining may also allow for subconscious emotions to be addressed and perhaps even future emotional states to be predicted. Minddistrict is currently studying the potential of emotion mining in association with Maastricht University. In the third stage, the flow of realtime assessment data is used to train a reinforcement learning algorithm that will adapt the frequency, timing, content and intervention medium to the unique characteristics of the client. At this stage, algorithms are utilised that would ‘learn’ which momentary states predict certain behaviours and which mobile interventions influence these momentary states in the desired direction.

Smart self-managementAn algorithm would for instance ‘learn’ that if during the evening, a certain client assesses his current self-esteem as less than four out of seven, he is more likely to abuse alcohol and also that a certain audioclip is most likely to lift his self-esteem. If in addition, analysis indicated that the user is more likely to experience low self-esteem on a specific day of the week, the audioclip may be offered early on those evenings as an attempt to avert low self-esteem. Reinforcement learning could also occur across individuals, in which an intervention strategy with the highest probability of reward for each individual is offered, based on an analysis of what worked best for previous users of the system with similar assessment data.

Because of the multi-media capabilities of mobile devices, the intelligent, real-time, interventions may consist of text, audio/video clips, photos and voice recordings, among other media. Although initially offered with profes-sional guidance, this smart intervention also allows for a greater degree of self-management by clients.

Minddistrict is seeking alliances with academia to develop this next genera-tion of online interventions. Will you join us?

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