About Behapp

Behapp is first-and-foremost a research instrument for use in (medical) scientific research contexts. Behapp facilitates the collection of personal smartphone-based data that is descriptive of one’s social behavior in terms of mobility and communication.

Our aim is to quantify human behavior using such objective, longitudinal and high resolution data streams which will help to:

  • Advance our understanding of (mental) disease and (brain) disorders
  • Detect changes in human behavior (e.g., to detect relapses)
  • Study the impact of (new) therapeutic interventions
  • Develop new digital biomarkers

We offer Behapp as a service to academic and / or medical institutions, CRO’s and pharmaceutical companies. Behapp has been specifically designed for ease of use and ease of integration in (existing) research projects, with support for multi-center and multi-phase studies. Additionally, we provide regulatory documentation, tech support, training for study managers and assistance with drafting up IRB documentation. 

Data collection

Behapp uses an app on the participant's device to track certain data.

Image of the Behapp app on a Samsung Galaxy S10
Screenshots of Behapp on a Samsung Galaxy S10.
Android
iOS
Active Data Collection
EMA / ESM
Yes
Yes
Passive Data Collection
Location
Yes
Yes
Calls
Yes
No
Texts
Yes
No
WiFi AP Scans
Yes
No
Screen States
Yes
No
Realtime app usage
Yes
No
Ambient Light
Yes
No

Administrative dashboard

Add, manage and keep track of your participants through the administrative dashboard.

An image of a laptop showing examples of the Behapp administrative portal for study managers

Research output

Our research is centered around the development of digital markers for behavior based on actively and passively collected smartphone - and / or wearable data.  Through active Experienced Sampling Methods, we generate quantitative and qualitative participant responses in a longitudinal manner. In addition, through passive remote monitoring, we generate longitudinal, quantitative, real-world and objective measures of behavior.

For example, we are developing digital markers for social functioning on the basis of behavioral features derived from digital data.  In support of this goal we work on a continuously evolving catalog of behavioral endpoints which represent quantitative behavioral features such as: 1) the number of unique places a participant has visited and; 2) the time spent using social media apps.

Example of changes in mobility

We studied how lockdown measures during the onset of the pandemic affected the mobility of research participants. As expected both the total number of unique places visited as well as the range of travel in general declined as shown on the right (Jagesar et al., 2021).

pre-lockdown
post-lockdown
To preserve privacy of our participants all datapoints have been aggregated and re-centered around a new reference point of 0,0.

Security & Privacy

Your data is yours. We only serve formal (medical) scientific initiatives. The handling, processing and subsequent distribution of study data will always be in accordance with predetermined (consortium) agreements. As such we will never share your data with unauthorized third parties.

To safeguard the privacy of your participants we make sure to adhere to the principles of zero trust and least privileges in the design of our technical service components. Furthermore, all measurement data that is collected is fully encrypted in transit and at rest.

For more information on how we handle your data, please take a look at our privacy policy.

Research cost

Fair share pricing with an emphasis on enabling valuable research

The costs of running a study depend on the sample size, duration, number of sites, localization requirements and additional data science efforts that are required. This may range from 25 kEU upwards to 100 kEU+ for funded and commercial research projects.

However, we realize that not all research is equally funded. For these initiatives we have additional research capacity available on our platform at a reduced rate. In any case, if you are interested in using Behapp for your research please contact us. We are interested in hearing about your ideas.

The team

Prof. dr. Martien Kas
Behavioural Neuroscience
Faculty of Science & Engineering
(University of Groningen)
Jacob Vorstman, M.D., PhD
(Child) Psychiatry
Department of Psychiatry (University of Toronto)
Program in Genetics and Genome Biology (The Hospital for Sick Children Toronto)
Raj Jagesar
Information Science
Faculty of Science & Engineering
(University of Groningen)
Mila Roozen
Data Science
Faculty of Science & Engineering
(University of Groningen)
Andrea Costanzo, PhD
Data Science
Faculty of Science & Engineering
(University of Groningen)
Anna Langener
Data Science
Faculty of Science & Engineering
(University of Groningen)