A User-Centered Approach to an Evidence-Based Electronic Health Pain Management Intervention for People With Chronic Pain: Design and Development of EPIO

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Chronic pain conditions are complicated and challenging to live with. Electronic health (eHealth) interventions show promise in helping people cope with chronic illness, including pain. The success of these interventions depends not only on the technology and intervention content but also on the users’ acceptance and adherence. Involving all stakeholders (eg, patients, spouses, health care providers, designers, software developers, and researchers) and exploring their input and preferences in the design and development process is an important step toward developing meaningful interventions and possibly strengthening treatment outcomes.

Objective

The aim of this study was to design and develop a user-centered, evidence-based eHealth self-management intervention for people with chronic pain.

Methods

The study employed a multidisciplinary and user-centered design approach. Overall, 20 stakeholders from the project team (ie, 7 researchers, 5 editors, 7 software developers, and 1 user representative), together with 33 external stakeholders (ie, 12 health care providers, 1 health care manger, 1 eHealth research psychologist, and 17 patients with chronic pain and 2 of their spouses) participated in a user-centered development process that included workshops, intervention content development, and usability testing. Intervention content was developed and finalized based on existing evidence, stakeholder input, and user testing. Stakeholder input was examined through qualitative analyses with rapid and in-depth analysis approaches.

Results

Analyses from stakeholder input identified themes including a need for reliable, trustworthy, and evidence-based content, personalization, options for feedback, behavioral tracking, and self-assessment/registration as factors to include in the intervention. Evidence-based intervention content development resulted in one face-to-face introduction session and 9 app-based educational and exercise-based modules. Usability testing provided further insight into how to optimize the design of the intervention to the user group, identifying accessibility and a simple design to be essential.

Conclusions

The design and development process of eHealth interventions should strive to combine well-known evidence-based concepts with stakeholder input. This study, designing and developing the pain management intervention EPIO, illustrates how a stakeholder-centered design approach can provide essential input in the development of an eHealth self-management intervention for people with chronic pain.

Trial Registration

ClinicalTrials.gov NCT03705104; https://clinicaltrials.gov/ct2/show/NCT03705104

Related collections

Most cited references 46

Record: found
Abstract: found
Article: found

Is Open Access

Persuasive System Design Does Matter: A Systematic Review of Adherence to Web-Based Interventions

Saskia M Kelders, Robin N Kok, Hans Ossebaard … (2013)

Background Although web-based interventions for promoting health and health-related behavior can be effective, poor adherence is a common issue that needs to be addressed. Technology as a means to communicate the content in web-based interventions has been neglected in research. Indeed, technology is often seen as a black-box, a mere tool that has no effect or value and serves only as a vehicle to deliver intervention content. In this paper we examine technology from a holistic perspective. We see it as a vital and inseparable aspect of web-based interventions to help explain and understand adherence. Objective This study aims to review the literature on web-based health interventions to investigate whether intervention characteristics and persuasive design affect adherence to a web-based intervention. Methods We conducted a systematic review of studies into web-based health interventions. Per intervention, intervention characteristics, persuasive technology elements and adherence were coded. We performed a multiple regression analysis to investigate whether these variables could predict adherence. Results We included 101 articles on 83 interventions. The typical web-based intervention is meant to be used once a week, is modular in set-up, is updated once a week, lasts for 10 weeks, includes interaction with the system and a counselor and peers on the web, includes some persuasive technology elements, and about 50% of the participants adhere to the intervention. Regarding persuasive technology, we see that primary task support elements are most commonly employed (mean 2.9 out of a possible 7.0). Dialogue support and social support are less commonly employed (mean 1.5 and 1.2 out of a possible 7.0, respectively). When comparing the interventions of the different health care areas, we find significant differences in intended usage (p = .004), setup (p < .001), updates (p < .001), frequency of interaction with a counselor (p < .001), the system (p = .003) and peers (p = .017), duration (F = 6.068, p = .004), adherence (F = 4.833, p = .010) and the number of primary task support elements (F = 5.631, p = .005). Our final regression model explained 55% of the variance in adherence. In this model, a RCT study as opposed to an observational study, increased interaction with a counselor, more frequent intended usage, more frequent updates and more extensive employment of dialogue support significantly predicted better adherence. Conclusions Using intervention characteristics and persuasive technology elements, a substantial amount of variance in adherence can be explained. Although there are differences between health care areas on intervention characteristics, health care area per se does not predict adherence. Rather, the differences in technology and interaction predict adherence. The results of this study can be used to make an informed decision about how to design a web-based intervention to which patients are more likely to adhere.

0 comments Cited 570 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Cognitive behavior therapy via the Internet: a systematic review of applications, clinical efficacy and cost-effectiveness.

Erik Hedman, Brjánn Ljótsson, Nils Lindefors (2012)

Internet-based cognitive behavior therapy (ICBT) is a promising treatment that may increase availability of cognitive behavior therapy (CBT) for psychiatric disorders and other clinical problems. The main objective of this study was to determine the applications, clinical efficacy and cost-effectiveness of ICBT. The authors conducted a systematic review to identify randomized controlled trials investigating CBT delivered via the internet for adult patient populations. Searches to identify studies investigating cost-effectiveness of ICBT were also conducted. Evidence status for each clinical application was determined using the American Psychologist Association criteria for empirically supported treatments. Of 1104 studies reviewed, 108 met criteria for inclusion, of which 103 reported on clinical efficacy and eight on cost-effectiveness. Results showed that ICBT has been tested for 25 different clinical disorders, whereas most randomized controlled trials have been aimed at depression, anxiety disorders and chronic pain. Internet-based treatments for depression, social phobia and panic disorder were classified as well-established, that is, meeting the highest level of criteria for evidence. Effect sizes were large in the treatment of depression, anxiety disorders, severe health anxiety, irritable bowel syndrome, female sexual dysfunction, eating disorders, cannabis use and pathological gambling. For other clinical problems, effect sizes were small to moderate. Comparison to conventional CBT showed that ICBT produces equivalent effects. Cost-effectiveness data were relatively scarce but suggested that ICBT has more than 50% probability of being cost effective compared with no treatment or to conventional CBT when willingness to pay for an additional improvement is zero. Although ICBT is a promising treatment option for several disorders, it can only be regarded as a well-established treatment for depression, panic disorder and social phobia. It seems that ICBT is as effective as conventional CBT for respective clinical disorder, that is, if conventional CBT works then ICBT works. The large effects and the limited therapist time required suggest that the treatment is highly cost effective for well-established indications.

0 comments Cited 246 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Factors Determining the Success and Failure of eHealth Interventions: Systematic Review of the Literature

Conceição Granja, Wouter Janssen, Monika Alise Johansen (2018)

Background eHealth has an enormous potential to improve healthcare cost, effectiveness, and quality of care. However, there seems to be a gap between the foreseen benefits of research and clinical reality. Objective Our objective was to systematically review the factors influencing the outcome of eHealth interventions in terms of success and failure. Methods We searched the PubMed database for original peer-reviewed studies on implemented eHealth tools that reported on the factors for the success or failure, or both, of the intervention. We conducted the systematic review by following the patient, intervention, comparison, and outcome framework, with 2 of the authors independently reviewing the abstract and full text of the articles. We collected data using standardized forms that reflected the categorization model used in the qualitative analysis of the outcomes reported in the included articles. Results Among the 903 identified articles, a total of 221 studies complied with the inclusion criteria. The studies were heterogeneous by country, type of eHealth intervention, method of implementation, and reporting perspectives. The article frequency analysis did not show a significant discrepancy between the number of reports on failure (392/844, 46.5%) and on success (452/844, 53.6%). The qualitative analysis identified 27 categories that represented the factors for success or failure of eHealth interventions. A quantitative analysis of the results revealed the category quality of healthcare (n=55) as the most mentioned as contributing to the success of eHealth interventions, and the category costs (n=42) as the most mentioned as contributing to failure. For the category with the highest unique article frequency, workflow (n=51), we conducted a full-text review. The analysis of the 23 articles that met the inclusion criteria identified 6 barriers related to workflow: workload (n=12), role definition (n=7), undermining of face-to-face communication (n=6), workflow disruption (n=6), alignment with clinical processes (n=2), and staff turnover (n=1). Conclusions The reviewed literature suggested that, to increase the likelihood of success of eHealth interventions, future research must ensure a positive impact in the quality of care, with particular attention given to improved diagnosis, clinical management, and patient-centered care. There is a critical need to perform in-depth studies of the workflow(s) that the intervention will support and to perceive the clinical processes involved.

0 comments Cited 218 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Lise Solberg Nes:

ORCID: https://orcid.org/0000-0002-9261-0871

Department of Digital Health ResearchDivision of MedicineOslo University HospitalPb 4950 NydalenOslo, N-0424Norway47 91332341lise.solberg.nes@rr-research.no

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (iso-abbrev): J. Med. Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: January 2020

Publication date (Electronic): 21 January 2020

Volume: 22

Issue: 1

Electronic Location Identifier: e15889

Affiliations

[1 ] Department of Digital Health Research Division of Medicine Oslo University Hospital Oslo Norway

[2 ] Institute of Clinical Medicine Faculty of Medicine University of Oslo Oslo Norway

[3 ] Science Centre Health and Technology University of South-Eastern Norway Drammen Norway

[4 ] Norwegian National Advisory Unit on Learning and Mastery in Health Oslo University Hospital Oslo Norway

[5 ] Centre for eHealth and Wellbeing Research University of Twente Enschede Netherlands

[6 ] Department of Clinical and Health Psychology University of Florida Gainesville, FL United States

[7 ] Department of Anesthesiology and Pain Medicine School of Medicine University of Washington Seattle, WA United States

[8 ] Department of Psychiatry and Psychology Mayo Clinic Rochester, MN United States

[9 ] Center for Learning and Mastery Bærum Hospital Vestre Viken Hospital Trust Bærum Norway

[10 ] National Advisory Unit on Rehabilitation in Rheumatology Department of Rheumatology Diakonhjemmet Hospital Oslo Norway

[11 ] Faculty of Health VID Specialized University Oslo Norway

[12 ] Regional Advisory Unit on Pain Oslo University Hospital Oslo Norway

Author notes

Corresponding Author: Lise Solberg Nes lise.solberg.nes@ 123456rr-research.no

Author information

Ingrid Konstanse Ledel Solem https://orcid.org/0000-0003-1684-3048

Cecilie Varsi https://orcid.org/0000-0001-5257-7993

Hilde Eide https://orcid.org/0000-0003-4428-5047

Olöf Birna Kristjansdottir https://orcid.org/0000-0002-8585-5547

Elin Børøsund https://orcid.org/0000-0003-3897-7055

Karlein M G Schreurs https://orcid.org/0000-0002-1229-0151

Lori B Waxenberg https://orcid.org/0000-0003-4987-8503

Karen E Weiss https://orcid.org/0000-0001-6576-0615

Eleshia J Morrison https://orcid.org/0000-0002-2872-943X

Mette Haaland-Øverby https://orcid.org/0000-0002-3629-9898

Katherine Bevan https://orcid.org/0000-0002-9289-3509

Heidi Andersen Zangi https://orcid.org/0000-0001-6882-221X

Audun Stubhaug https://orcid.org/0000-0002-0606-8001

Lise Solberg Nes https://orcid.org/0000-0002-9261-0871

Article

Publisher ID: v22i1e15889

DOI: 10.2196/15889

PMC ID: 7001051

PubMed ID: 31961331

SO-VID: 6e2c8d2e-a44d-492f-a054-1301025329b7

Copyright © ©Ingrid Konstanse Ledel Solem, Cecilie Varsi, Hilde Eide, Olöf Birna Kristjansdottir, Elin Børøsund, Karlein M G Schreurs, Lori B Waxenberg, Karen E Weiss, Eleshia J Morrison, Mette Haaland-Øverby, Katherine Bevan, Heidi Andersen Zangi, Audun Stubhaug, Lise Solberg Nes. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 21.01.2020.

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 10 September 2019

Date revision requested : 1 October 2019

Date revision received : 18 October 2019

Date accepted : 16 December 2019

Comments

Comment on this article

scite_

Cited by 24

See all cited by

Most referenced authors 694

See all reference authors

Submit your digital health research with an established publisher
- celebrating 25 years of open access