Behavioral Study to Predict the Efficacy of a Self-Help Tool

The study aims to examine whether the investigators can predict, on the level of individual participants who have symptoms of depression, who will benefit more from self-help tools based on principles of behavioral activation vs. cognitive restructuring, in terms of a greater decrease of self-reported symptoms. The investigators use a combination of self-reported clinical information and behavior on learning and decision-making tasks to predict change in symptom scores.

Study Overview

• Status: Active, not recruiting
• Conditions: Self-reported Symptoms of Depression
• Intervention / Treatment: Behavioral: Self-help information based on principles of behavioral activation; Behavioral: Self-help information based on principles of cognitive restructuring

Detailed Description

Background:

Cognitive-Behavioral Therapy (CBT) is a learning-based psychotherapy treatment that has been established as effective treatment for depression. It consists of two core interventions: cognitive restructuring (CR) and behavioral activation (BA). In recent years, internet-delivered CBT (iCBT) has been developed, which allows for dissemination of standardized, evidence-based, CBT treatments at scale.

Virtually all psychotherapy methods aim to teach clients something new: new behavioral or thought patterns, new responses to triggers and situations, and/or new emotional reactions. As such, learning-based psychotherapies modify targeted brain circuits to the extent that these circuits show flexibility and are amenable to change through learning. The human brain has several learning circuits/mechanisms that work in parallel. Different people will have more flexibility and learn more effectively through some learning mechanisms and not others. Because different psychotherapy methods (e.g., BA and CR) rely on different types of learning, the investigators hypothesize that by characterizing what learning mechanisms are most available and efficient for each person, will allow us to predict what intervention method will be most effective for that person.

The goal of this study is to test if people's individual learning propensities can predict what type of intervention will benefit them more.

Detailed study design:

In a fully online study, the investigators deploy several behavioral tasks to assess individual differences in learning and decision-making processes. Participants then get access to an internet-based self-help tool for depression that is based on CBT principles, and are asked to undergo either the BA modules or the CR modules (random assignment; 5 weeks of 1-hour session per week). The investigators follow up on symptoms at the middle of the period of use of the self-help tool (at this point, some behavioral tasks are repeated as well), at the end of this period, and at different times up to a year after finishing use of the self-help tool.

Participants are recruited online via advertisement, for instance on social media. After checking eligibility and obtaining consent online, participants are randomized to be part of the discovery or validation dataset (the investigators will not analyze the validation dataset until all analyses are pre-registered). Participants are then asked to fill out a range of symptom self-report questionnaires and complete a series of behavioral tasks. They are then randomized to either a cognitive restructuring group or behavioral activation group. All participants are then given access to e-couch, a validated self-help tool. In the first week, all participants complete the depression information submodule from the depression program. Over the following four weeks, participants in the cognitive restructuring group complete submodules on cognitive restructuring and participants in the behavioral activation group complete submodules on behavioral activation and physical activity. After that period, participants are free to engage with any of the other modules e-couch offers. Participants are additionally asked to fill out symptom self-report questionnaires 1,3,5,12,24 and 48 weeks after the start of e-couch engagement, and to repeat a subset of the behavioral tasks 3 weeks after the start of e-couch engagement.

All interaction with participants is conducted online via email (and possibly via zoom to verify identity or technical advice) and online-administered tasks, questionnaires and the self-help tool. The investigators do not offer any medical advice and forward participants to appropriate sources of support (e.g., hotlines) if needed.

Quality assurance plan:

All data are collected online through our in-house custom-built software. The code for the assessments has been reviewed and data quality has been checked prior to study start. The code is backed up on a secure server and the investigators can make the code available for review to relevant authorities.

Data checks:

The investigators use a range of attention checks throughout the study to exclude data from inattentive participants or participants who respond randomly.

Statistical analysis plan:

Note, the goal of this study is not to assess how much the self-help tools affect symptoms on average. This has been examined previously (and will only be verified in this dataset). The primary goal of this study is to develop a tool that predicts for a new individual (whose data was not part of the tool development, i.e. out-of-sample) what interventions they may benefit more from.

When consenting, participants are assigned to a discovery or a validation dataset. After completing analyses on the discovery dataset, the investigators will pre-register a detailed statistical analysis plan and apply that to the validation dataset to confirm and verify any findings. Below is the general approach to analyzing the discovery data:

Step 1) Compute scores for the self-report scales in line with the literature and fit computational models to data from the behavioral task to retrieve individual model parameters that best explain behavior the behavior from each participant.

Step 2) Use prediction models, e.g. elastic nets, to predict from the above parameters and scores, symptom scores (in particular, for depression and anhedonia) from each participant at the end of the engagement with the self-help tool and during follow ups, and/or improvement of symptom scores from before to after the engagement with the self-help tool.

Step 3) Examine whether change in task behavior due to the first half of engagement with the self-help tool mediates a change in symptoms from before to after that engagement.

• Study Type: Interventional
• Enrollment (Estimated): 1500
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • New Jersey
    • Princeton, New Jersey, United States, 08540
      • Princeton Neuroscience Institute, but recruitment and study are conducted completely online and can occur anywhere in the US.

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Fluent in English
• The primary mental health concern participants want to work on must be that they would like to improve their mood, to reduce negative thoughts, to enjoy more activities again and/or to reduce symptoms of depression
• Having a picture ID and be willing to meet with us on a video zoom call for identity verification if invited to do so

Exclusion Criteria:

• Lack of attention when completing parts of the study, lack of honesty or not completing parts of the study in a timely way
• Identity check failure

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Double

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Behavioral activation group; Participants will read information and engage in exercises through the self-help tool e-couch that aim at stimulating their engagement in pleasant activities.	Behavioral: Self-help information based on principles of behavioral activation; Participants will engage with the self-help tool e-couch (https://ecouch.com.au). In the first week, they will complete the depression information submodule from the depression program. Over the following four weeks, they will complete submodules on behavioral activation and physical activity.
Experimental: Cognitive restructuring group; Participants will read information and engage in exercises through the self-help tool e-couch that aim at tackling negative thinking.	Behavioral: Self-help information based on principles of cognitive restructuring; Participants will engage with the self-help tool e-couch (https://ecouch.com.au). In the first week, they will complete the depression information submodule from the depression program. Over the following four weeks, they will complete submodules on cognitive restructuring.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Predictive accuracy of sum of self-reported depression symptoms (assessed with Patient Health Questionnaire) after engagement with self-help tool using behavioral tasks	Participants will be randomized to a discovery or validation datasets with a ratio of 2:1. Prior to analyzing the validation dataset, the investigators will pre-register the precise analyses based on the results from the discovery dataset. Participants complete several behavioral tasks focusing on learning and decision-making prior to start of the engagement with the self-help tool. Self-reported depression symptom scores are assessed with the Patient Health Questionnaire (PHQ-9, sum ranges from 0-27, higher scores indicate more symptoms of depression). The investigators will predict change in depression symptoms based on modeled task data and then verify the results in pre-registered analyses of the validation dataset.	approx. 6 weeks
Predictive accuracy of sum of self-reported anhedonia symptoms (assessed with Snaith-Hamilton Pleasure scale) after engagement with self-help tool using behavioral tasks	Participants will be randomized to a discovery or validation datasets with a ratio of 2:1. Prior to analyzing the validation dataset, the investigators will pre-register the precise analyses based on the results from the discovery dataset. The participants complete several behavioral tasks focusing on learning and decision-making prior to start of the engagement with the self-help tool. Self-reported symptoms scores of anhedonia will be assessed with the Snaith-Hamilton Pleasure Scale (SHAPS, sum score range from 14-56, higher scores indicate more anhedonia). The investigators will predict change in anhedonia symptoms based on task data and then verify the results in pre-registered analyses of the validation dataset.	approx. 6 weeks

Collaborators and Investigators

• Sponsor: Trustees of Princeton University

Study record dates

Study Major Dates

• Study Start (Actual): January 23, 2024
• Primary Completion (Estimated): December 1, 2025
• Study Completion (Estimated): December 1, 2025

Study Registration Dates

• First Submitted: September 24, 2024
• First Submitted That Met QC Criteria: October 4, 2024
• First Posted (Actual): October 8, 2024

Study Record Updates

• Last Update Posted (Actual): April 10, 2025
• Last Update Submitted That Met QC Criteria: April 7, 2025
• Last Verified: April 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Behavioral Symptoms; Depression
• Other Study ID Numbers: 15118

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Researchers will share de-identified questionnaire data and behavioral task data with other researchers from the Wellcome Leap consortium and after publication with other researcher upon reasonable request.
• IPD Sharing Time Frame: Within one year after study completion, some data may be shared earlier.
• IPD Sharing Access Criteria: Upon reasonable request and providing that the requesters will treat the data in line with the researchers' ethical principles. Researchers may also make de-identified data publicly available.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; ICF; ANALYTIC_CODE

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No