Are E-Mental Health Applications for Depression Beneficial?

Research Paper Title

E-mental health applications for depression: an evidence-based ethical analysis.


E-mental health applications (apps) are an increasingly important factor for the treatment of depression.

To assess the risks and benefits for patients, an in-depth ethical analysis is necessary.

The objective of this paper is to determine the ethical implications of app-based treatment for depression.


An evidence-based ethical analysis was conducted.

The material was meta-reviews and randomised control studies (RCTs) on app-based treatment.

Based on the empirical data, an ethical analysis was conducted using the 3-ACES-approach by Thornicroft and Tansella.


Apps may empower autonomy, offer an uninterrupted series of contacts over a period of time, show evidence-based benefits for patients with subclinical and mild-to-moderate-symptoms, are easily accessible, may be used for coordinating information and services within an episode of care, and are on the whole cost-effective.

Their risks are that they are not suitable for the whole range of severity of mental illnesses and patient characteristics, show severe deficits in the data privacy policy, and a big variability in quality standards.


The use of apps in depression treatment can be beneficial for patients as long as:

  • The usefulness of an app-based treatment is assessed for each individual patient;
  • Apps are chosen according to symptom severity as well as characteristics like the patient’s level of self-reliance, their e-literacy, and their openness vis-à-vis apps; and
  • Manufacturers improve their privacy policies and the quality of apps.


Rubeis, G. (2020) E-mental health applications for depression: an evidence-based ethical analysis. European Archives of Psychiatry and Clinical Neuroscience. doi: 10.1007/s00406-019-01093-y. [Epub ahead of print].

Leave a Reply

Please log in using one of these methods to post your comment: Logo

You are commenting using your account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.