Use and Appreciation of a Tailored Self-Management eHealth Intervention for Early Cancer Survivors: Process Evaluation of a Randomized Controlled Trial

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Abstract

Background

A fully automated computer-tailored Web-based self-management intervention, Kanker Nazorg Wijzer (KNW [Cancer Aftercare Guide]), was developed to support early cancer survivors to adequately cope with psychosocial complaints and to promote a healthy lifestyle. The KNW self-management training modules target the following topics: return to work, fatigue, anxiety and depression, relationships, physical activity, diet, and smoking cessation. Participants were guided to relevant modules by personalized module referral advice that was based on participants’ current complaints and identified needs.

Objective

The aim of this study was to evaluate the adherence to the module referral advice, examine the KNW module use and its predictors, and describe the appreciation of the KNW and its predictors. Additionally, we explored predictors of personal relevance.

Methods

From the respondents (N=231; mean age 55.6, SD 11.5; 79.2% female [183/231]), 98.3% (227/231) were referred to one or more KNW modules (mean 2.9, SD 1.5), and 85.7% (198/231) of participants visited at least one module (mean 2.1, SD 1.6). Significant positive associations were found between the referral to specific modules (range 1-7) and the use of corresponding modules. The likelihoods of visiting modules were higher when respondents were referred to those modules by the module referral advice. Predictors of visiting a higher number of modules were a higher number of referrals by the module referral advice (β=.136, P=.009), and having a partner was significantly related with a lower number of modules used (β=-.256, P=.044). Overall appreciation was high (mean 7.5, SD 1.2; scale 1-10) and was significantly predicted by a higher perceived personal relevance (β=.623, P=.000). None of the demographic and cancer-related characteristics significantly predicted the perceived personal relevance.

Results

The KNW in general and more specifically the KNW modules were well used and highly appreciated by early cancer survivors. Results indicated that the module referral advice might be a meaningful intervention component to guide the users in following a preferred selection of modules. These results indicate that the fully automated Web-based KNW provides personal relevant and valuable information and support for early cancer survivors. Therefore, this intervention can complement usual cancer aftercare and may serve as a first step in a stepped-care approach.

Conclusions

The KNW in general and more specifically the KNW modules were well used and highly appreciated by early cancer survivors. Indications were found that the module referral advice might be a meaningful intervention component to guide the users in following a preferred selection of modules. These results indicate that the fully automated Web-based KNW provides personal relevant and valuable information and support for early cancer survivors. Therefore, this intervention can complement usual cancer aftercare and may serve as a first step in a stepped-care approach.

Trial Registration

Nederlands Trial Register: NTR3375; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3375 (Archived by WebCite at http://www.webcitation.org/6jo4jO7kb)

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Most cited references 47

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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.

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Jan H.M.M. Vercoulen, Caroline Swanink, Jan F.M. Fennis … (1994)

The absence of laboratory tests and clear criteria to identify homogeneous (sub)groups in patients presenting with unexplained fatigue, and to assess clinical status and disability in these patients, calls for further assessment methods. In the present study, a multi-dimensional approach to the assessment of chronic fatigue syndrome (CFS) is evaluated. Two-hundred and ninety-eight patients with CFS completed a set of postal questionnaires that assessed the behavioural, emotional, social, and cognitive aspects of CFS. By means of statistical analyses nine relatively independent dimensions of CFS were identified along which CFS-assessment and CFS-research can be directed. These dimensions were named: psychological well-being, functional impairment in daily life, sleep disturbances, avoidance of physical activity, neuropsychological impairment, causal attributions related to the complaints, social functioning, self-efficacy expectations, and subjective experience of the personal situation. A description of the study sample on these dimensions is presented.

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A behavior change model for internet interventions.

Lee Ritterband, Frances Thorndike, Daniel Cox … (2009)

The Internet has become a major component to health care and has important implications for the future of the health care system. One of the most notable aspects of the Web is its ability to provide efficient, interactive, and tailored content to the user. Given the wide reach and extensive capabilities of the Internet, researchers in behavioral medicine have been using it to develop and deliver interactive and comprehensive treatment programs with the ultimate goal of impacting patient behavior and reducing unwanted symptoms. To date, however, many of these interventions have not been grounded in theory or developed from behavior change models, and no overarching model to explain behavior change in Internet interventions has yet been published. The purpose of this article is to propose a model to help guide future Internet intervention development and predict and explain behavior changes and symptom improvement produced by Internet interventions. The model purports that effective Internet interventions produce (and maintain) behavior change and symptom improvement via nine nonlinear steps: the user, influenced by environmental factors, affects website use and adherence, which is influenced by support and website characteristics. Website use leads to behavior change and symptom improvement through various mechanisms of change. The improvements are sustained via treatment maintenance. By grounding Internet intervention research within a scientific framework, developers can plan feasible, informed, and testable Internet interventions, and this form of treatment will become more firmly established.

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Author and article information

Contributors

Iris Maria Kanera:

Faculty of Psychology and Educational SciencesOpen University of the NetherlandsValkenburgerweg 177Heerlen, 6401 DLNetherlands31 455762448iris.kanera@ou.nl

ORCID: http://orcid.org/0000-0001-6863-2096

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: August 2016

Publication date (Electronic): 23 August 2016

Volume: 18

Issue: 8

Electronic Location Identifier: e229

Affiliations

[1] ¹Faculty of Psychology and Educational Sciences Open University of the Netherlands HeerlenNetherlands

[2] ²Research Institute CAPHRI Department of Epidemiology, Optimizing Patient Care Maastricht University MaastrichtNetherlands

[3] ³Department of Urology Zuyderland Medical Center Heerlen and Sittard-GeleenNetherlands

[4] ⁴Netherlands Comprehensive Cancer Organisation (IKNL) UtrechtNetherlands

Author notes

Corresponding Author: Iris Maria Kanera iris.kanera@ 123456ou.nl

Author information

Iris Maria Kanera http://orcid.org/0000-0001-6863-2096

Roy A Willems http://orcid.org/0000-0002-5775-3367

Catherine A W Bolman http://orcid.org/0000-0001-9209-6449

Ilse Mesters http://orcid.org/0000-0001-8940-5271

Victor Zambon http://orcid.org/0000-0002-7578-9806

Brigitte CM Gijsen http://orcid.org/0000-0003-4578-0293

Lilian Lechner http://orcid.org/0000-0002-5160-7086

Article

Publisher ID: v18i8e229

DOI: 10.2196/jmir.5975

PMC ID: 5013245

PubMed ID: 27554525

SO-VID: 93977041-2ac3-47dd-a586-16fbcb967c28

Copyright © ©Iris Maria Kanera, Roy A Willems, Catherine A W Bolman, Ilse Mesters, Victor Zambon, Brigitte CM Gijsen, Lilian Lechner. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 23.08.2016.

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), 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 : 17 May 2016

Date revision requested : 2 June 2016

Date revision received : 11 July 2016

Date accepted : 20 July 2016

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