Using Machine Learning to Optimize User Engagement and Clinical Response to Digital Mental Health Interventions

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorBoston University Charles River Campus

About this trial

Digital mental health interventions are a cost-effective and efficient approach to expanding the accessibility and impact of psychological treatments; however, little guidance exists for selecting the most effective program for a given individual. In the proposed study, decision rules will develop for selecting the digital program that is most likely to be the optimal intervention for each user. These treatment recommendations can be implemented in the context of large healthcare delivery systems to improve the delivery of digital mental health interventions at scale.

The overarching aim of the current study is to better understand for whom and how leading digital interventions work in a large healthcare setting. The study builds on the existing literature and follows expert recommendations by using machine learning (ML) methods to develop precision treatment rules (PTRs) for three leading digital interventions for emotional disorders (e.g., anxiety, depression, and related mental health disorders). Specifically, ML methods will be used to develop PTRs to optimize clinical outcomes and associated intervention engagement. This study will leverage a unique partnership between Boston University (BU), SilverCloud Health (SC)--a leading provider of digital mental health care--and Kaiser Permanente (KP)--one of America's leading health care providers.

A clinical trial (RCT) will be conducted to evaluate the relative effectiveness of three distinct empirically supported digital mental health interventions (from SC's existing library of programs) in a sample recruited from KP primary care and other clinical settings. Data from this trial will be used to develop theoretically and empirically informed, reliable selection algorithms for managing treatment delivery decisions. Algorithms will be validated in a separate "holdout" dataset by examining whether allocation to predicted optimal treatment is associated with superior outcomes compared to allocation to a non-optimal treatment. The role of user engagement will be determined, and other mechanisms in treatment outcome.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

English-speaking adults

Ages 18 or older

Have a device that can connect to the internet.

Disqualifiers

None

Trial design

Design model

Parallel

Treatments tested in this trial

  • The Unified Protocol for Transdiagnostic Treatment of Emotional Disorders (UP)

    Behavioral

    This is a cognitive behavioral treatment (CBT) for emotional disorders. This transdiagnostic intervention consists of eight modules and can be effectively applied to various disorders and problems.

  • Space for depression

    Behavioral

    Digital CBT program designed to minimize the impact of depression symptoms. Emphasizes CBT strategies and mindfulness through a series of seven structured modules.

  • Space for resilience

    Behavioral

    This program is built from positive psychology principles and is designed to promote resilience and well-being through seven modules.

Treatment groups

1,800 Participants
are divided into 3 treatment groups
Group A: The Unified Protocol for Transdiagnostic Treatment of Emotional Disorders (UP)Experimental treatment 1 intervention
Group B: Space from Depression (SFD)Active comparator 1 intervention
Group C: Space for Resilience (SFR)Active comparator 1 intervention

Trial outcomes

Primary outcomes

1

Change from baseline well-being at week 12

World Health Organization-Five (WHO-5) is a 5-item self-report questionnaire of psychological well being. The WHO-5 has demonstrated good validity and utility as an outcome measure in clinical trials including several digital intervention trials. Respondents rate each statement in relation to the past two weeks on a scale ranging from 0= At no time to 5= All the time (Ware, 1995).

Time frame
Baseline, 4-weeks following baseline, 8-weeks following baseline, and 12-weeks following baseline

Secondary outcomes

1

Change from baseline anxiety at week 12

Generalized Anxiety Disorder-7 (GAD-7) is a reliable and valid self-report measure of symptoms of generalized anxiety that is widely used in clinical research. This measures consists of 7 questions in a likert scale format, and respondents rate each question on a scale ranging 0=Not at all or 3= Nearly every day, indicating how often they experience anxiety-related problems (Spitzer, Kroenke, Williams, Lowe, 2006).

Time frame
Baseline, 4-weeks following baseline, 8-weeks following baseline, and 12-weeks following baseline
2

Change in baseline depression at week 12

Patient Health Questionnaire 9 (PHQ-9) is a reliable and valid self-report measure of depression symptoms that is widely used in clinical research. Consisting of 9 questions, respondents rate each question on a scale ranging 0= Not at all or 3= Nearly every day, indicating how often they experience depression-related problems (Pfizer, 1999).

Time frame
Baseline, 4-weeks following baseline, 8-weeks following baseline, and 12-weeks following baseline

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Boston University Charles River Campus

Lead sponsor

National Institute of Mental Health (NIMH)

Collaborator

Silver Cloud Health

Collaborator

Kaiser Permanente

Collaborator