Literature DB >> 31705515

Digital Interventions for Mental Disorders: Key Features, Efficacy, and Potential for Artificial Intelligence Applications.

David Daniel Ebert1, Mathias Harrer2, Jennifer Apolinário-Hagen3, Harald Baumeister4.   

Abstract

Mental disorders are highly prevalent and often remain untreated. Many limitations of conventional face-to-face psychological interventions could potentially be overcome through Internet-based and mobile-based interventions (IMIs). This chapter introduces core features of IMIs, describes areas of application, presents evidence on the efficacy of IMIs as well as potential effect mechanisms, and delineates how Artificial Intelligence combined with IMIs may improve current practices in the prevention and treatment of mental disorders in adults. Meta-analyses of randomized controlled trials clearly show that therapist-guided IMIs can be highly effective for a broad range of mental health problems. Whether the effects of unguided IMIs are also clinically relevant, particularly under routine care conditions, is less clear. First studies on IMIs for the prevention of mental disorders have shown promising results. Despite limitations and challenges, IMIs are increasingly implemented into routine care worldwide. IMIs are also well suited for applications of Artificial Intelligence and Machine Learning, which provides ample opportunities to improve the identification and treatment of mental disorders. Together with methodological innovations, these approaches may also deepen our understanding of how psychological interventions work, and why. Ethical and professional restraints as well as potential contraindications of IMIs, however, should also be considered. In sum, IMIs have a high potential for improving the prevention and treatment of mental health disorders across various indications, settings, and populations. Therefore, implementing IMIs into routine care as both adjunct and alternative to face-to-face treatment is highly desirable. Technological advancements may further enhance the variability and flexibility of IMIs, and thus even further increase their impact in people's lives in the future.

Entities:  

Keywords:  Artificial intelligence; Internet interventions; Machine learning; Mental disorders; Prevention; Psychotherapy; eHealth

Mesh:

Year:  2019        PMID: 31705515     DOI: 10.1007/978-981-32-9721-0_29

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  12 in total

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Authors:  Renaldo M Bernard; Claudia Toppo; Alberto Raggi; Marleen de Mul; Carlota de Miquel; Maria Teresa Pugliese; Christina M van der Feltz-Cornelis; Ana Ortiz-Tallo; Luis Salvador-Carulla; Sue Lukersmith; Leona Hakkaart-van Roijen; Dorota Merecz-Kot; Kaja Staszewska; Carla Sabariego
Journal:  J Med Internet Res       Date:  2022-06-01       Impact factor: 7.076

2.  Engagement in digital interventions.

Authors:  Inbal Nahum-Shani; Steven D Shaw; Stephanie M Carpenter; Susan A Murphy; Carolyn Yoon
Journal:  Am Psychol       Date:  2022-03-17

3.  Automatic detection of depression symptoms in twitter using multimodal analysis.

Authors:  Ramin Safa; Peyman Bayat; Leila Moghtader
Journal:  J Supercomput       Date:  2021-09-09       Impact factor: 2.557

4.  AI in patient flow: applications of artificial intelligence to improve patient flow in NHS acute mental health inpatient units.

Authors:  Fatema Mustansir Dawoodbhoy; Jack Delaney; Paulina Cecula; Jiakun Yu; Iain Peacock; Joseph Tan; Benita Cox
Journal:  Heliyon       Date:  2021-05-12

5.  Advantages and disadvantages of online and blended therapy: Replication and extension of findings on psychotherapists' appraisals.

Authors:  Raphael Schuster; Naira Topooco; Antonia Keller; Ella Radvogin; Anton-Rupert Laireiter
Journal:  Internet Interv       Date:  2020-05-07

6.  Effect of an internet- and app-based stress intervention compared to online psychoeducation in university students with depressive symptoms: Results of a randomized controlled trial.

Authors:  Mathias Harrer; Jennifer Apolinário-Hagen; Lara Fritsche; Christel Salewski; Anna-Carlotta Zarski; Dirk Lehr; Harald Baumeister; Pim Cuijpers; David Daniel Ebert
Journal:  Internet Interv       Date:  2021-02-24

Review 7.  Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review.

Authors:  Paulina Cecula; Jiakun Yu; Fatema Mustansir Dawoodbhoy; Jack Delaney; Joseph Tan; Iain Peacock; Benita Cox
Journal:  Heliyon       Date:  2021-04-15

8.  Exploring medical students' views on digital mental health interventions: A qualitative study.

Authors:  Melina Dederichs; Jeannette Weber; Claudia R Pischke; Peter Angerer; Jennifer Apolinário-Hagen
Journal:  Internet Interv       Date:  2021-04-30

9.  Decreasing mental well-being during the COVID-19 pandemic: A longitudinal study among Danes before and during the pandemic.

Authors:  Lau Caspar Thygesen; Sanne Pagh Møller; Annette Kjær Ersbøll; Ziggi Ivan Santini; Maj Britt Dahl Nielsen; Morten Klöcker Grønbæk; Ola Ekholm
Journal:  J Psychiatr Res       Date:  2021-09-23       Impact factor: 5.250

10.  Piloting sexual assault care centres in Belgium: who do they reach and what care is offered?

Authors:  Saar Baert; Christine Gilles; Sara Van Belle; Iva Bicanic; Kristien Roelens; Ines Keygnaert
Journal:  Eur J Psychotraumatol       Date:  2021-07-27
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