NiceDay Research Vision
Since the birth of NiceDay in 2017, our main aim has been to push online mental healthcare to the next level making it more effective for clients while keeping it cost-effective. We have been discovering the multiple benefits that this digital mental healthcare service has brought us: a more effective treatment for clients in need of mental support, an improved therapist's workflow, and a greater reach and impact to society. Many research questions have been proposed since then in a wide variety of topics. Some of them have already been answered but there is still a lot of work that remains to be done. This is why here in NiceDay we are interested in working together with other teams who want to make significant contributions to mental healthcare and strive for effective, accessible and affordable care for all. Below, we will further explain our vision, methods and some of the topics we want to further address and learn more about:
Data-driven approach
The NiceDay-app offers a platform that is available at any time and place, and can be used for online or blended care, perfectly fitting our hybrid and dynamic society. The way of working with the service – the NiceDayWay - is based on conditioning paradigms and the network theory of psychopathology. When working according to the NiceDayWay, patients are actively involved in the therapeutic process by tracking and registering symptoms in their daily life. By using this experience sampling methodology, patients and therapists are allowed to get an 'in the moment' account of the patients’ subjective experiences and to contextualize these in terms of psychological, social and environmental factors. This network of factors is visualized for both therapists and patients, and quickly provides insight into the relationship between symptoms, vulnerabilities and resilience. This helps therapists to conduct the most appropriate evidence-based interventions at the most optimal time. This gain in momentum increases the learning effect, the generalizability , and the ecological validity of these interventions. Furthermore, these insights can already be incorporated into a relapse prevention plan during treatment, which reduces the likelihood of a return of symptoms - a major problem within mental health care.
Improving therapists workflow
Therapists are trained to adopt the NiceDay way and make effective use of the service tools or features that facilitate this way of working, for example, by using a flexible agenda in which they can check clients recent activity and current mental state on a dashboard outside of the scheduled meetings and contact them when necessary or when it seems most effective. This allows therapists to connect and keep track of clients naturally and easily.
The client can also use chat functions to maintain regular contact with their therapist. This method of working increases insight into the (interrelationship between) complaints and stimulates an equal relationship between patient and therapist, inducing patient autonomy and improving the therapeutic alliance.
Measure client progress
Autonomy is further promoted by evaluating on a regular basis, preferably before each scheduled meeting, whether the treatment is still on track. This is done by inviting the patient to fill in two very short questionnaires before and after each meeting: The Outcome Measure Questionnaire (OMQ) and Session Measure Questionnaire (SMQ). These measure client progress and the working alliance respectively. They are based on Feedback Informed Therapy and there is sufficient evidence that shows the benefits of keeping track in near real-time what is and is not working in treatment[1][2], and therefore gives the possibility of making data-supported refinements in the treatment plan.
Optimizing treatment
Our main research objective is to investigate the separate ingredients of the NiceDayWay of working (e.g., use of diary, chat-functions, outcome feedback, and frequency of in-between session contact) to analyze what each of them add to the effectiveness of interventions. Outcome parameters will not only be client-related, e.g., decrease in symptoms and increase of quality of life, but also therapist-related. Therapist-related parameters concern for example to the sense of control they experience on the treatment process, job satisfaction but also their productivity: is the NiceDayWay a (cost)effective way of treating patients?
This is also where – in the future - Artificial Intelligence (AI) and Machine Learning can play an important role. Continuous data-input offers us the possibility to develop AI-based decision-support tools for therapists. We could develop algorithms that learn from datasets to then generate models that can detect ‘signal cases’ and make predictions of the best fitting evidence-based interventions. In this way therapists are supported to provide the optimal treatment and to prevent therapeutic ‘drifting’: a major problem in mental health care resulting in patients not (optimally) receiving the treatment they deserve, with all entailing personal and social consequences. We believe that developing an AI-decision tool increases the (cost)effectiveness of treatments also by keeping therapists ‘on-track’ and improving their skills.
If you are interested in research collaboration with NiceDay, please click here for more information.