Tailoring Persuasive Electronic Health Strategies for Older Adults on the Basis of Personal Motivation: Web-Based Survey Study

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Abstract

Background

Persuasive design, in which the aim is to change attitudes and behaviors by means of technology, is an important aspect of electronic health (eHealth) design. However, selecting the right persuasive feature for an individual is a delicate task and is likely to depend on individual characteristics. Personalization of the persuasive strategy in an eHealth intervention therefore seems to be a promising approach.

Objective

This study aimed to develop a method that allows us to model motivation in older adults with respect to leading a healthy life and a strategy for personalizing the persuasive strategy of an eHealth intervention, based on this user model.

Methods

We deployed a Web-based survey among older adults (aged >60 years) in the Netherlands. In the first part, we administered an adapted version of the revised Sports Motivation Scale (SMS-II) as input for the user models. Then, we provided each participant with a selection of 5 randomly chosen mock-ups (out of a total of 11), each depicting a different persuasive strategy. After showing each strategy, we asked participants how much they appreciated it. The survey was concluded by addressing demographics.

Results

A total of 212 older adults completed the Web-based survey, with a mean age of 68.35 years (SD 5.27 years). Of 212 adults, 45.3% were males (96/212) and 54.7% were female (116/212). Factor analysis did not allow us to replicate the 5-factor structure for motivation, as targeted by the SMS-II. Instead, a 3-factor structure emerged with a total explained variance of 62.79%. These 3 factors are intrinsic motivation, acting to derive satisfaction from the behavior itself (5 items; Cronbach alpha=.90); external regulation, acting because of externally controlled rewards or punishments (4 items; Cronbach alpha=.83); and a-motivation, a situation where there is a lack of intention to act (2 items; r=0.50; P<.001). Persuasive strategies were appreciated differently, depending on the type of personal motivation. In some cases, demographics played a role.

Conclusions

The personal type of motivation of older adults (intrinsic, externally regulated, and/or a-motivation), combined with their educational level or living situation, affects an individual’s like or dislike for a persuasive eHealth feature. We provide a practical approach for profiling older adults as well as an overview of which persuasive features should or should not be provided to each profile. Future research should take into account the coexistence of multiple types of motivation within an individual and the presence of a-motivation.

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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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Brief questions to identify patients with inadequate health literacy.

Lisa Chew, Katharine A Bradley, Edward Boyko (2004)

No practical method for identifying patients with low heath literacy exists. We sought to develop screening questions for identifying patients with inadequate or marginal health literacy. Patients (n=332) at a VA preoperative clinic completed in-person interviews that included 16 health literacy screening questions on a 5-point Likert scale, followed by a validated health literacy measure, the Short Test of Functional Health Literacy in Adults (STOHFLA). Based on the STOFHLA, patients were classified as having either inadequate, marginal, or adequate health literacy. Each of the 16 screening questions was evaluated and compared to two comparison standards: (1) inadequate health literacy and (2) inadequate or marginal health literacy on the STOHFLA. Fifteen participants (4.5%) had inadequate health literacy and 25 (7.5%) had marginal health literacy on the STOHFLA. Three of the screening questions, "How often do you have someone help you read hospital materials?" "How confident are you filling out medical forms by yourself?" and "How often do you have problems learning about your medical condition because of difficulty understanding written information?" were effective in detecting inadequate health literacy (area under the receiver operating characteristic curve of 0.87, 0.80, and 0.76, respectively). These questions were weaker for identifying patients with marginal health literacy. Three questions were each effective screening tests for inadequate health literacy in this population.

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Understanding tailoring in communicating about health.

Robert Hawkins, Matthew K Kreuter, Kenneth Resnicow … (2008)

'Tailoring' refers to any of a number of methods for creating communications individualized for their receivers, with the expectation that this individualization will lead to larger intended effects of these communications. Results so far have been generally positive but not consistently so, and this paper seeks to explicate tailoring to help focus future research. Tailoring involves either or both of two classes of goals (enhancing cognitive preconditions for message processing and enhancing message impact through modifying behavioral determinants of goal outcomes) and employs strategies of personalization, feedback and content matching. These goals and strategies intersect in a 2 x 3 matrix in which some strategies and their component tactics match better to some goals than to others. The paper illustrates how this framework can be systematically applied in generating research questions and identifying appropriate study designs for tailoring research.

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Author and article information

Contributors

Lex van Velsen:

ORCID: http://orcid.org/0000-0003-0599-8706

eHealth GroupRoessingh Research and DevelopmentPO Box 310Enschede, 7500 AHNetherlands31 0880875754l.vanvelsen@rrd.nl

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: September 2019

Publication date (Electronic): 06 September 2019

Volume: 21

Issue: 9

Electronic Location Identifier: e11759

Affiliations

[1 ] eHealth Group Roessingh Research and Development Enschede Netherlands

[2 ] Biomedical Signals and Systems Group University of Twente Enschede Netherlands

Author notes

Corresponding Author: Lex van Velsen l.vanvelsen@ 123456rrd.nl

Author information

Lex van Velsen http://orcid.org/0000-0003-0599-8706

Marijke Broekhuis http://orcid.org/0000-0003-4954-7640

Stephanie Jansen-Kosterink http://orcid.org/0000-0002-2095-7104

Harm op den Akker http://orcid.org/0000-0001-6312-6063

Article

Publisher ID: v21i9e11759

DOI: 10.2196/11759

PMC ID: 6788334

PubMed ID: 31493323

SO-VID: 3ea7957c-e96a-4425-9854-2313f2766c2c

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 : 1 August 2018

Date revision requested : 9 October 2018

Date revision received : 31 January 2019

Date accepted : 25 May 2019

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