Ecological momentary interventions in psychiatry

Inez Myin-Germeys*, Annelie Klippel, Henrietta Steinhart, Ulrich Reininghaus

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Purpose of review In this review, we discuss feasibility, content, and where possible efficacy of ecological momentary interventions (EMIs) in psychiatry. EMIs adopt mobile devices, such as personal digital assistants or smartphones, for the delivery of treatments in the daily life of patients. We will discuss EMIs in the field of schizophrenia, bipolar disorder and major depression disorder, as well as one generic, transdiagnostic EMI. Recent findings The few studies that are available all underscore feasibility and acceptability of mobile health approaches in patients with severe mental illness. In terms of content, there is a huge variety in approaches ranging from a mixture of face-to-face contacts augmented with EMI components to a fully automated EMI. With regard to efficacy, only two randomized clinical trials have been conducted, supporting the efficacy of EMIs in mental health. Evidence seems to point toward greater efficacy when EMI is integrated with real-life assessment using experience sampling methodology, preferentially tailoring the intervention toward the specific needs of the individual as well as toward those moments when intervention is needed. Summary The review demonstrates that mobile health may be an important asset to the mental health field but underscores that it still is in its very early ages. In the discussion, we point toward ways of improving EMIs for severe mental illness, changing our perspective from testing feasibility to testing efficacy and ultimately implementing EMIs in routine mental health services.
Original languageEnglish
Pages (from-to)258-263
JournalCurrent Opinion in Psychiatry
Volume29
Issue number4
DOIs
Publication statusPublished - Jul 2016

Keywords

  • ecological momentary interventions
  • experience sampling methodology
  • mHealth
  • severe mental illness

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