Cited by 19Digital Mental Health InterventionsMobile Health and mHealth ApplicationsInnovative Human-Technology Interaction

mHealth in Mental Health: how to efficiently and scientifically create an ambulatory biofeedback e-coaching app for patients with borderline personality disorder

Derks, Youri P.M.J., Visser, Tessa De, Bohlmeijer, Ernst T., Noordzij, Matthijs L.·2017·International Journal of Human Factors and Ergonomics

Abstract

mHealth applications aim to 'coach' users in achieving a better life. However, many of these e-coaches are not based on sound background knowledge of those in need of support. One such group is patients with a borderline personality disorder (BPD). Patients with BPD experience great difficulties in regulating their emotions, in part due to an inability to recognise (changes in) emotions. Using a modified UXD-framework, we investigated the need amongst BPD-patients and therapists for an ambulatory biofeedback e-coaching app that supports patients in learning to better recognise changes in their arousal level. This study adds: 1) a 'design science' approach to developing mHealth applications; 2) the insight that needs of both groups did converge to a degree, but mental models differed fundamentally; 3) a set of requirements for a physiologically based real-time biofeedback tool for psychiatric patients; 4) personas that can form the basis for other research within this group.

Integrity signals

Registry

Crossref · 10.1504/ijhfe.2017.088418

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Eliciting requirements from target groups comprising patients who are vulnerable and clinically complex, such as people with psychosis or dementia, might be challenging.

    “Third, it was mentioned that eliciting requirements from target groups comprising patients who are vulnerable and clinically complex, such as people with psychosis or dementia, might be challenging.”
  • Multiple authors indicated that card sorting is a fast, efficient, and cheap method to gain insight into the structure of a to-be-developed eHealth technology, especially when conducted on the web.

    “Multiple authors indicated that card sorting is a fast, efficient, and cheap method to gain insight into the structure of a to-be-developed eHealth technology, especially when conducted on the web”
  • To structure the persona-building process, researchers need to identify characteristic categories that need to be included in the persona, in which attention should also be paid to skills and attitudes related to the to-be-developed eHealth technology.

    “Second, to structure the persona-building process, researchers need to identify characteristic categories that need to be included in the persona, in which attention should also be paid to skills and attitudes related to the to-be-developed eHealth technology.”

Cited by

Sorted by citations

Authors
Derks, Y. P. M. J., Visser, T. D., Bohlmeijer, E. T., & Noordzij, M. L.
Affiliations
  • GGNet (NL)
  • University of Twente (NL)
Venue
International Journal of Human Factors and Ergonomics
Published
2017
Volume
5
Issue
1
Pages
61
ISSN
  • 2045-7804 (ISSN-L)
  • 2045-7812
OpenAlex
W4239092382
Cited by
19
References
0
Citations by year
2024: 1 · 2023: 1 · 2022: 4 · 2021: 6 · 2020: 1 · 2019: 3 · 2018: 3
FWCI
2.20
Type
journal article
Language
en
Open access
closed
Locations
  • International Journal of Human Factors and Ergonomics (publishedVersion)
  • University of Twente Research Information (publishedVersion)
  • University of Twente Research Information (submittedVersion)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
mobile health, borderline personality disorder, biofeedback, emotion regulation, user needs analysis, mental models, personas, design science

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review