Literature DB >> 31894391

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

Giovanni Rubeis1.   

Abstract

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 randomized 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 (1) the usefulness of an app-based treatment is assessed for each individual patient, (2) 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, (3) manufacturers improve their privacy policies and the quality of apps.

Entities:  

Keywords:  Apps; Blended therapy; Depressive disorders; E-mental health; Ethics; Treatment gap

Year:  2020        PMID: 31894391     DOI: 10.1007/s00406-019-01093-y

Source DB:  PubMed          Journal:  Eur Arch Psychiatry Clin Neurosci        ISSN: 0940-1334            Impact factor:   5.270


  2 in total

1.  The Digital Therapeutic Alliance and Human-Computer Interaction.

Authors:  Simon D'Alfonso; Reeva Lederman; Sandra Bucci; Katherine Berry
Journal:  JMIR Ment Health       Date:  2020-12-29

2.  A Conversational Artificial Intelligence Agent for a Mental Health Care App: Evaluation Study of Its Participatory Design.

Authors:  Morena Danieli; Seyed Mahed Mousavi; Giuseppe Riccardi; Tommaso Ciulli
Journal:  JMIR Form Res       Date:  2021-12-01
  2 in total

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