Sally+ Preventing Depression in Singaporean Students
The lifetime prevalence of almost all mental disorders in Singapore is rising. Young people seem to be a particularly vulnerable group as they are more likely to have mental health disorders. Unfortunately, there is also a significant treatment gap among people with mood, anxiety and alcohol use disorders in Singapore. FHT’s Mobile Health Interventions module investigates how mobile chatbot technology can be leveraged to assist individuals in preventing depression from a public health perspective. MobileCoach, an open-source platform that relies on an automated conversational agent (chatbot) to deliver scalable, interactive and engaging mobile health interventions, will be used in this project to address this challenge. The overall goal of this project is therefore to build an effective digital mental health coach Sally+ who helps individuals with subclinical depression (we plan to target the population of students from NTU, as part of the Healthy Campus Initiative).
In particular, Sally+ has the following distal outcome goals:
- To improve quality of life,
- To reduce depressive symptoms
- To reduce the risk of developing major depressive disorder
To reach these goals, Sally+ aims to build a working alliance with individuals with subclinical depression (i.e. a shared understanding about treatment goals and tasks, and attachment bond, which is robustly linked to treatment success and will apply coaching strategies that are personalized according (1) to an individual’s preferences in lifestyle behaviour and (2) to the current stage of change. To do so, the coaching of Sally+ will primarily rely on cognitive behavioural therapy. Moreover, Sally+ will be adapted to the characteristics of the population and the healthcare ecosystem in Singapore with a specific focus on the healthy campus initiative at NTU.
To carry out this research, the multiphase optimization strategy (MOST) will be applied. In the preparation phase, we will conduct a literature review, interviews and focus group discussions with individuals suffering from subclinical depression, mental health experts and (potential) future providers of Sally+. To identify the most effective intervention components (Furukawa et al., 2018) with respect to the distal outcomes, Sally+ is then assessed, as part of the optimization phase of MOST, with the help of a micro-randomized trial with individuals suffering from subclinical depression.
Based on the results of that optimization trial, final revisions to Sally+ will be made, and, as part of the last evaluation phase, an RCT will be employed in the last two years to assess the effectiveness and cost-effectiveness of Sally+.
Project overview by:
Dr. Jacqueline Mair
Dr. Alicia Salamanca-Sanabria
M.Sc. Aishah Alattas
Project updates by:
M.Sc. Aishah Alattas
M.Sc. Jiali Yao
M.Sc. Roman Keller
Meeting facilitated by:
Senior Scientist Dr. Jacqueline Mair PhD
Teepe, G., Da Fonseca, A., Kleim, B., Jacobson, N.C., Salamanca-Sanabria, A., Tudor Car, L., Fleisch, E., Kowatsch, T. (2021) Just-in-Time Adaptive Mechanisms of Popular Mobile Apps for Individuals With Depression: Systematic App Search and Literature Review, Journal of Medical Internet Research (JMIR) 23(9):e29412, 10.2196/29412, Visual Abstract by G. Teepe. [PDF]
Alattas, A., Teepe, G., Leidenberger, K., Fleisch, E., Tudor Car, L., Salamanca-Sanabria, A., Kowatsch, T. (2021) To what scale are conversational agents used by top-funded companies offering digital mental health services for depression? In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) – Volume 5: HEALTHINF, 801-808 (PDF)
Tudor Car, L., Ardhithy Dhinagaran, D., Kyaw, B.M., Kowatsch, T., Joty, S.R., Theng, Y.L., Atun, R. (2020) Conversational Agents in Health Care: A Scoping Review and Conceptual Analysis (2020) Journal of Medical Internet Research, 22(8):e17158, 10.2196/17158. (PDF)
Schachner, T., Keller, R., von Wangenheim, F. (2020) Artificial Intelligence-Based Conversational Agents for Chronic Conditions: Systematic Literature Review, Journal of Medical Internet Research;22(9):e20701, 10.2196/20701. (PDF)
Video Abstract by:
M.Sc. Aishah Alattas