Clinical Targets and Attitudes Toward Implementing Digital Health Tools for Remote Measurement in Treatment for Depression: Focus Groups With Patients and Clinicians

Valeria de Angel, Serena Lewis, Katie M. White, Faith Matcham, Matthew Hotopf

Research output: Contribution to journalArticlepeer-review

5 Citations (SciVal)


Background: Remote measurement technologies, such as smartphones and wearable devices, can improve treatment outcomes for depression through enhanced illness characterization and monitoring. However, little is known about digital outcomes that are clinically meaningful to patients and clinicians. Moreover, if these technologies are to be successfully implemented within treatment, stakeholders’ views on the barriers to and facilitators of their implementation in treatment must be considered. Objective: This study aims to identify clinically meaningful targets for digital health research in depression and explore attitudes toward their implementation in psychological services. Methods: A grounded theory approach was used on qualitative data from 3 focus groups of patients with a current diagnosis of depression and clinicians with >6 months of experience with delivering psychotherapy (N=22). Results: Emerging themes on clinical targets fell into the following two main categories: promoters and markers of change. The former are behaviors that participants engage in to promote mental health, and the latter signal a change in mood. These themes were further subdivided into external changes (changes in behavior) or internal changes (changes in thoughts or feelings) and mapped with potential digital sensors. The following six implementation acceptability themes emerged: technology-related factors, information and data management, emotional support, cognitive support, increased self-awareness, and clinical utility. Conclusions: The promoters versus markers of change differentiation have implications for a causal model of digital phenotyping in depression, which this paper presents. Internal versus external subdivisions are helpful in determining which factors are more susceptible to being measured by using active versus passive methods. The implications for implementation within psychotherapy are discussed with regard to treatment effectiveness, service provision, and patient and clinician experience.

Original languageEnglish
Article numbere38934
JournalJMIR mental health
Issue number8
Early online date15 Aug 2022
Publication statusPublished - 31 Aug 2022
Externally publishedYes

Bibliographical note

Funding Information:
MH is the principal investigator of the Remote Assessment of Disease and Relapse–Central Nervous System program, a precompetitive public-private partnership funded by the Innovative Medicines Initiative and the European Federation of Pharmaceutical Industries and Associations.

Funding Information:
This study represents independent research funded by the National Institute for Health and Care Research Biomedical Research Centre in South London and Maudsley National Health Service Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the National Health Service, the National Institute for Health and Care Research, or the Department of Health and Social Care. The funders of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the manuscript.


  • depression
  • digital health tools
  • digital phenotyping
  • implementation
  • mHealth
  • mobile health
  • mobile phone
  • mood disorders
  • passive sensing
  • qualitative
  • sensor data
  • smartphone
  • wearable devices

ASJC Scopus subject areas

  • Psychiatry and Mental health


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