“EMA is poised not only to replace clinician-administered rating scales in research settings but also to increase accessibility of EMA measures to the patients and health care providers in clinical settings, ultimately allowing real-world clinical settings to contribute meaningful data to research and development of new interventions.”
from 
When All Else Fails, Listen to the Patient, 2019.

There is a mental health crisis in the developed world – 1 in 5 US adults suffer from mental illness each year, suicide is the 2nd leading cause of death amongst 10-34 year olds – and yet the vast majority of funding for drug development goes to diseases with identifiable biological targets. Why?

In part, this is because it is extremely difficult to capture mental health symptom change using traditional clinical trial methodology. Many clinical trial fail late stage and are unable to demonstrate drug efficacy but a major factor in this is the way patient outcomes are being measured – not the viability of the drug. 

Traditional clinical trial methodology has relied on clinician reported measures taken before and after a period of drug treatment. Researchers have identified four key reasons that this methods isn’t effective at capturing mental health symptom change (Mofsen et al., 2019):

– Inappropriately broad measures that attempt to capture much more than the drug is targeting
Recall bias: it relies on patients remembering how they felt day and weeks ago
Poor inter-rater reliability: clinicians often don’t agree on how to score the same patient
– Limitations of distinguishing between State and Trait factors of a mental health disorder    

The use of Ecological Momentary Assessment can solve many of these problems in pharmaceutical clinical trials.

Benefits of Ecological Momentary Assessment in Clinical Trials

Reduces Bias

PROs more effective than clinician ratings

Reduces recall bais

Reduces social desirability bias 

 

Frequent Sampling = Increased Sensitivity

Capture symptom fluctuation throughout the day and over treatment course

 Less complex measures are more sensitive to change
 

Leads to Precision Medicine

Discover temporal dynamics of symptom change for responders and non-responders

 Develop personalized just-in-time interventions to support drug treatment

EMA Reduces Bias

EMA relies on patient reported outcomes rather than clinician ratings. Historically it has been assumed that clinician ratings are more objective that patient reported outcomes but Uher et al (2012) found that self-report measures contributed more to the prediction of clinician reported measures than visa versa and concluded that if only one form of measurement can be used that self-report is the best choice. Additionally, a large meta-analysis found that clinician administered scales were associated with a higher placebo response that Patient Reported Outcomes (PROs) which they attributed to the social desirability bias – i.e. the patients’ desire to provide the answer they think the clinician wants to hear (Mora et al., 2011).

Recall bias is a major problem and well documented. People don’t remember very accurately what happened in the past – especially when it comes to how they felt. Ecological Momentary Assessment has been shown to be more effective than retrospective report in pain (Stone et al., 2005), affect (Parkinson et al., 1995) and major depressive disorder (van Rijsbergen et al., 2014). 

More Frequent Sampling leads to Increased Sensitivity

The infrequent sampling of traditional clinical trial methods (pre and post treatment) is not only impacted by recall bias but flattens response effects. It assumes that we know how a disorder behaves over time, which we don’t (Mofsen et al., 2019). Symptoms of depression have been shown to fluctuate throughout the day by using EMA (Peeters, et al., 2006) as has impulsivity in bipolar patients (Depp et al., 2015).  EAM allows researchers to track the temporal fluctuation in symptoms in relation to medication ingestion. 

EMA allows for frequent sampling (often multiple times a day) which provides a data granularity unprecedented in mental health drug trials. In addition to tracking temporal fluctuation the high sampling rate requires that measures be simplified – to reduce patient burden. Simpler measures, that target core symptoms only, have been found to be more sensitive to detecting assay response than traditional scales. For instance, EMA has found treatment effects that the traditional scales in major depressive disorder were unable to detect (Barge- Schaapveld & Nicolson, 2020). 

In a direct comparison of traditional paper-and-pencil methods of tracking anxiety and depression symptoms and EMA with older adults participating in a Mindfulness Based Stress Reduction intervention, EMA was found to be much more sensitive in detecting change. The Number-to-Treat (NTT) scores from EMA were 15-50% lower than scores from pencil-and-paper methods (Moore et al., 2016).

Precision Medicine and Just-in-Time Intervention

Baseline scores in clinical trials are often inflated (due to bias as discussed above) and then return to “normal” over the course of treatment, thus reducing the observed treatment effect. EMA methods can be used to determine a more ecologically valid baseline, and thus increase sensitivity to change, than traditional methods. EMA can be used to take repeated measures throughout the baseline period in addition to tracking context (e.g. at work, at home, daily stressors, interpersonal conflict, menstrual cycle, weather, time of day, etc.) to provide a baseline mean, range and standard deviation that is more reflective of the patient’s experience. Variance from this baseline can then be tracked continuously throughout the treatment period to understand better how the drug interacts with symptoms. This can be done for each individual patient leading us to precision medicine 

In the wider mental health field EMA has been used in the development of EMI – Ecological Momentary Interventions- whereby intervention content is delivered via Smartphone to the patient throughout their daily life. When combined with machine learning algorithms that make decisions about which piece of content to deliver at which time EMIs become “just-in-time adaptive interventions” – highly precise behavioral interventions designed to change behavior in the moment. Used in combination with drug treatments JITAI’s hold the promise of dramatically increasing positive outcomes for many struggling with mental health.

Features

Create your Study with no Programming Experience

There is no need to wait for us to build anything – it’s already built! After a one hour online training session you will be able to create all your mobile surveys, set up notification schedules for each participant and turn on or off sensor data streams.

Make your Intervention “Just-in-Time”

The mEMA app can make decisions about which intervention content to present to which participant at which moment. Just tell us which data streams to use, define the decision logic and we will do all the rest. 

Focus on your Research Knowing you are Supported

Our Customer Support team are here to help you by email or phone at any point in your study. If changes to the Apple or Android operating system impact your study in any way we will take care of it immediately. 

Ensure your Data are Secure and Compliant

We will make sure your study stays compliant with HIPAA, GDPR and 21 CFR Part 11

Our Founders

Kat Houghton PhD
Co-Founder and CEO
Psychologist; Behavioral Intervention Specialist

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Mark Tuomenoksa 
Co-Founder and CTO
Maverick inventor and musician with a passion for making the world a better place

Frequently Asked Questions and Concerns

What distinguishes you from everyone else?

There are very few commercially available EMA platforms. We are the only one that offers access to phone sensors, media capture, geotracking, audio tracking, and integrate with wearable devices. We are the only commercially available platform that can be used to run a Just-in-Time Adaptive Intervention

Who are you guys anyway?

We’re psychologists and software engineers who know how to speak both languages!

What results will I actually get from this?

An easy way to set up your study, let the data roll in and not have to deal with the technical headaches.

What exactly am I signing up for?

The full list of features for the three pricing levels is here. After your strategy session we can guide you to the license level that’s the best fit for your study.

Are there any long-term contracts? 

You can subscribe to the mEMA System for 6 months, 1 year or more. The Terms and Conditions are here

How do I present this to my team?

Send them to this page and invite them to join the Strategy Session

What wearables does it integrate with?

Currently Garmin (Vidiosmart 4) and Emaptica (E4 and Embrace). We are always looking for more!

How do I know this will work for my study?

If after the Strategy Session you are still not sure then we can offer you a free trial.

Can I randomize the sampling rate of the EMA surveys?

Yes! There are multiple ways to set up the notification schedules – stratified randomization is one of them

Does the participant have to press upload every time they complete a survey?

Yes! There are multiple ways to set up the notification schedules – stratified randomization is one of them

In what format do I download the data?

CSV file. You will get a CSV for each survey and each sensor type you choose. Media (videos, photos, audio files) are stored separately and are downloaded in bulk as a .ZIP file per participant. The data files are dynamic and are updates each time a participant submits new data.

How much data will the mEMA app take up on my participant’s cellular data plan?

Each survey item (i.e. question or message) is 265 bits. So to calculate daily data usage: 265 x number of elements in each survey x number of surveys per day.