Elomia - Digital Mental Health and Well-Being

July 15, 2025 updated by: Melissa Hunt, PhD, University of Pennsylvania

Digital Mental Health and Well-Being

This study is testing the acceptability and efficacy of an AI enabled mental health chatbot (Elomia) as a resource of college student wellness.

Study Overview

Detailed Description

Elomia is a generative AI program that can respond to text users type in with unique responses that are designed to address therapeutic targets like stress, anxiety, procrastination, feeling overwhelmed and so on. Elomia was "trained" by real therapists with expertise in cognitive-behavioral therapy who responded to many different real people typing about their concerns. Thus, Elomia can suggest a number of different evidence based therapeutic strategies and can help the user process negative feelings, think through problems, plan solutions, and trouble shoot things that might get in the way of implementing those strategies. Elomia's arsenal includes:

  • exercises for calming;
  • exercises for falling asleep;
  • grounding techniques;
  • exercises to reduce anxiety;
  • breathing exercises;
  • exercises to improve self-esteem. The algorithm determines the user's need for one or another type of help while communicating with the chatbot and suggests an exercise to ease their emotional state. Elomia is not a substitute for professional care, and will detect when a person needs something more than a chatbot and will suggest connecting with other resources. More information about Elomia can be found via this website: https://elomia.com/

The ultimate goal of this study is to explore whether a mental health chatbot is acceptable and can improve symptoms of depression, anxiety, stress, and promote general psychological well-being in college students. The investigators will compare Elomia to a curated collection of digital wellness resources that are typically provided to students at our University.

Study Type

Interventional

Enrollment (Actual)

63

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Pennsylvania
      • Philadelphia, Pennsylvania, United States, 19104
        • University of Pennsylvania

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Undergraduate student at the University of Pennsylvania.
  • At least 18 years of age.

Exclusion Criteria:

* Severe depression or suicidality as indicated by Beck Depression Inventory score of >= 30, and/or a score of 2 or 3 on the Item (the suicide item) of the Beck Depression Inventory

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Randomized
  • Interventional Model: Crossover Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Elomia - Digital Mental Health Chatbot
Participants randomized to Elomia will be expected to use the intervention at least once per week (for around 30 minutes) but are encouraged to use as needed/wanted. Elomia is a generative AI program that can respond to text the user types in with unique responses that are designed to address therapeutic targets like stress, anxiety, procrastination, feeling overwhelmed and so on. Elomia was "trained" by real therapists with expertise in cognitive-behavioral therapy who responded to many different real people typing about their concerns. Thus, Elomia can suggest a number of different evidence based therapeutic strategies and can help the user process negative feelings, think through problems, plan solutions, and trouble shoot things that might get in the way of implementing those strategies.
Elomia uses generative AI to respond to user input about psychological stress and distress. It was trained on the responses of real therapists with expertise in cognitive-behavioral therapy. It provides an array of wellness interventions including exercises for calming; • exercises for falling asleep; • grounding techniques; • exercises to reduce anxiety; • breathing exercises; • exercises to improve self-esteem.
Active Comparator: Penn Wellness Modules
Participants randomized to the control condition will be expected to use the intervention at least once per week (for around 30 minutes) but are encouraged to use as needed/wanted. The control condition consists of a curated collection of digital wellness resources that are already available freely to Penn students, including tips on getting good sleep, learning center material on time management and procrastination, and so on. The resources will be accessed via a single website, but there is no interactive component.
This active control intervention consists of a variety of digital wellness and stress management resources that are freely available to all Penn students.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Beck Depression Inventory
Time Frame: Baseline and 4 week follow-up
Self-report inventory of depressive symptoms Scores range from 0 to 63. Higher scores indicate more severe (worse) depressive symptoms.
Baseline and 4 week follow-up
GAD 7
Time Frame: Baseline and 4 week follow-up
Self-report inventory of symptoms of anxiety. Scores range from 0 to 21. Higher scores indicate more severe (worse) symptoms of anxiety.
Baseline and 4 week follow-up
Perceived Stress Scale
Time Frame: Baseline and 4 week follow-up
Self-report questionnaire of perceived stress. Scores range from 0 to 40. Higher scores indicate more severe (worse) perceived stress.
Baseline and 4 week follow-up

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Melissa G Hunt, PhD, University of Pennsylvania

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 15, 2025

Primary Completion (Actual)

May 30, 2025

Study Completion (Actual)

May 30, 2025

Study Registration Dates

First Submitted

December 5, 2024

First Submitted That Met QC Criteria

December 5, 2024

First Posted (Actual)

December 10, 2024

Study Record Updates

Last Update Posted (Actual)

July 18, 2025

Last Update Submitted That Met QC Criteria

July 15, 2025

Last Verified

July 1, 2025

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

To protect participant confidentiality

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

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Perceived Stress

Clinical Trials on AI enabled wellness chatbot

Subscribe