Overview
The goal of this research is to test usability and user satisfaction with a new breathing feature on the meditation app, Equa, to help young adults who are distressed, understand their physiological responses and mindfulness skill development during meditation.
Our main aims are to test an algorithm that can use physiologic signals to give feedback about how participant physiology is changing during guided lessons on the meditation app, Equa through:
- Assessing user satisfaction and usability
- Measuring how much participant mindfulness skills are improving
Participants will:
- Complete a survey about demographics, their thoughts and feelings before and after the mindfulness meditation program
- Complete 14 smartphone guided mindfulness meditation training units while physiological measures are being recorded
- A subset of participants will see a graph tracking their physiological responses from the guided meditation lesson and predictive mindfulness skill scores
- Complete a few brief questionnaires before and after mindfulness practices to understand potential changes in their mindfulness skills
Description
Investigators will recruit young adults to participate in a study to examine the usability and user satisfaction of respiration biosignal feedback during meditation through phone motion data and microphones within headphones. Interested participants will be screened on study inclusion/exclusion criteria: (1) aged 18-30 years, (2) interested in coming on site to complete 14 smartphone guided mindfulness meditation training units, (3) willing to be assigned to one of two conditions, (4) willing to wear physiological monitoring equipment and provide ratings of their training experience, (5) Not currently pregnant and (6) no current or previous diagnosis of psychosis or schizophrenia
Participants are told they are going to participate in a study that focuses on monitoring physiological responses during meditation. At the start of the study, participants will complete questions via an online survey focused on demographics, prior meditation experience, their thoughts and feelings as these may be informative to participants' meditation experience.
Participants will complete a few brief questionnaires to understand potential changes in mindfulness before and after select lessons. Participant physiological data will be recorded (E.g., heart rate) via smartphones and headphones to track physiologic dynamics. Additionally, the sensory shirt, made by Hexoskin Smart Sensors; AI, will also continuously measure physiologics via two inductive plethysmography (RIP) sensors. The Hexoskin shirt also tracks motion via a three-axis accelerometer. These measures will enable investigators to better understand mindfulness measures during meditation.
Following the guided meditation lessons, a subset of participants (the experimental group) will see a graph tracking their physiological responses from the guided meditation lesson and predictive mindfulness skill scores based on our algorithm development. The feedback chart is produced by the physiological measures tracked throughout the duration of the lesson, and is displayed within the Equa app, moments after the meditation lessons concludes. The control group will not see the graph tracking their physiological responses.
Eligibility
Inclusion Criteria:
- Ages 18-30 years of Age
- Fluent in English
- Psychological distress
- Willing to participate in guided meditation or stress management training.
- Willing and able to wear earbud headphones and a shirt which uses sensors to track motion and physiological measures.
- Willing to be randomized to one of two conditions
- Willing to provide ratings on their training experience
Exclusion Criteria:
- Currently pregnant
- Current or previous diagnosis with psychosis or schizophrenia